A Byte of Python
Swaroop C H
27 May 2013
Contents
8
1.1 Who Reads A Byte of Python? . . . . . . . . . . . . . . . . . . .
8
1.2 Academic Courses . . . . . . . . . . . . . . . . . . . . . . . . . . 11
1.3 License . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
1.4 Read Now . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
1.5 Buy the Book . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
1.6 Download . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
1.7 Read the book in your native language . . . . . . . . . . . . . . . 12
13
2.1 Who This Book Is For . . . . . . . . . . . . . . . . . . . . . . . . 13
2.2 History Lesson . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.3 Status Of The Book . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.4 Official Website . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.5 Something To Think About . . . . . . . . . . . . . . . . . . . . . 14
15
3.1 Features of Python . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.1.1 Simple . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.1.2 Easy to Learn . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.1.3 Free and Open Source . . . . . . . . . . . . . . . . . . . . 15
3.1.4 High-level Language . . . . . . . . . . . . . . . . . . . . . 16
1
3.1.5 Portable . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
3.1.6 Interpreted . . . . . . . . . . . . . . . . . . . . . . . . . . 16
3.1.7 Object Oriented . . . . . . . . . . . . . . . . . . . . . . . 16
3.1.8 Extensible . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.1.9 Embeddable . . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.1.10 Extensive Libraries . . . . . . . . . . . . . . . . . . . . . . 17
3.2 Python 2 versus 3 . . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.3 What Programmers Say . . . . . . . . . . . . . . . . . . . . . . . 18
18
4.1 Installation on Windows . . . . . . . . . . . . . . . . . . . . . . . 18
4.1.1 DOS Prompt . . . . . . . . . . . . . . . . . . . . . . . . . 18
4.1.2 Running Python prompt on Windows . . . . . . . . . . . 19
4.2 Installation on Mac OS X . . . . . . . . . . . . . . . . . . . . . . 20
4.3 Installation on Linux . . . . . . . . . . . . . . . . . . . . . . . . . 20
4.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
21
5.1 Using The Interpreter Prompt . . . . . . . . . . . . . . . . . . . . 21
5.2 Choosing An Editor . . . . . . . . . . . . . . . . . . . . . . . . . 22
5.3 Using A Source File . . . . . . . . . . . . . . . . . . . . . . . . . 23
5.3.1 Executable Python Programs . . . . . . . . . . . . . . . . 25
5.4 Getting Help . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
5.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
27
6.1 Comments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
6.2 Literal Constants . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
6.3 Numbers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
6.4 Strings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
6.4.1 Single Quote . . . . . . . . . . . . . . . . . . . . . . . . . 28
6.4.2 Double Quotes . . . . . . . . . . . . . . . . . . . . . . . . 28
2
6.4.3 Triple Quotes . . . . . . . . . . . . . . . . . . . . . . . . . 29
6.4.4 Strings Are Immutable . . . . . . . . . . . . . . . . . . . . 29
6.4.5 The format method . . . . . . . . . . . . . . . . . . . . . 29
6.5 Variable . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
6.6 Identifier Naming . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
6.7 Data Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
6.8 Object . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
6.9 How to write Python programs . . . . . . . . . . . . . . . . . . . 32
6.10 Example: Using Variables And Literal Constants . . . . . . . . . 32
6.10.1 Logical And Physical Line . . . . . . . . . . . . . . . . . . 33
6.10.2 Indentation . . . . . . . . . . . . . . . . . . . . . . . . . . 34
6.11 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
35
7.1 Operators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
7.1.1 Shortcut for math operation and assignment . . . . . . . 38
7.2 Evaluation Order . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
7.3 Changing the Order Of Evaluation . . . . . . . . . . . . . . . . . 39
7.4 Associativity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
7.5 Expressions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
7.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
41
8.1 The if statement . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
8.2 The while Statement . . . . . . . . . . . . . . . . . . . . . . . . . 43
8.3 The for loop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
8.4 The break Statement . . . . . . . . . . . . . . . . . . . . . . . . . 46
8.4.1 Swaroop’s Poetic Python . . . . . . . . . . . . . . . . . . 47
8.5 The continue Statement . . . . . . . . . . . . . . . . . . . . . . . 47
8.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
3
48
9.1 Function Parameters . . . . . . . . . . . . . . . . . . . . . . . . . 49
9.2 Local Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
9.3 Using The global Statement . . . . . . . . . . . . . . . . . . . . . 51
9.4 Default Argument Values . . . . . . . . . . . . . . . . . . . . . . 52
9.5 Keyword Arguments . . . . . . . . . . . . . . . . . . . . . . . . . 53
9.6 VarArgs parameters . . . . . . . . . . . . . . . . . . . . . . . . . 54
9.7 Keyword-only Parameters . . . . . . . . . . . . . . . . . . . . . . 54
9.8 The return Statement . . . . . . . . . . . . . . . . . . . . . . . . 55
9.9 DocStrings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
9.10 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
58
10.1 Byte-compiled .pyc files . . . . . . . . . . . . . . . . . . . . . . . 59
10.2 The from . . . import statement . . . . . . . . . . . . . . . . . . . 60
10.3 A module’s name . . . . . . . . . . . . . . . . . . . . . . . . . . 60
10.4 Making Your Own Modules . . . . . . . . . . . . . . . . . . . . . 61
10.5 The dir function . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
10.6 Packages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
10.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
65
11.1 List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
11.1.1 Quick Introduction To Objects And Classes . . . . . . . . 65
11.2 Tuple . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
11.3 Dictionary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
11.4 Sequence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
11.5 Set . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
11.6 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
11.7 More About Strings . . . . . . . . . . . . . . . . . . . . . . . . . 75
11.8 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
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76
12.1 The Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
12.2 The Solution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
12.3 Second Version . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
12.4 Third Version . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
12.5 Fourth Version . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
12.6 More Refinements . . . . . . . . . . . . . . . . . . . . . . . . . . 84
12.7 The Software Development Process . . . . . . . . . . . . . . . . . 84
12.8 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
13 Object Oriented Programming
85
13.1 The self . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
13.2 Classes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
13.3 Object Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
13.4 The init method . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
13.5 Class And Object Variables . . . . . . . . . . . . . . . . . . . . . 88
13.6 Inheritance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
13.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
94
14.1 Input from user . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
14.2 Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
14.3 Pickle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
14.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98
99
15.1 Errors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
15.2 Exceptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
15.3 Handling Exceptions . . . . . . . . . . . . . . . . . . . . . . . . . 100
15.4 Raising Exceptions . . . . . . . . . . . . . . . . . . . . . . . . . . 101
15.5 Try .. Finally . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
15.6 The with statement . . . . . . . . . . . . . . . . . . . . . . . . . 103
15.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
5
104
16.1 sys module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
16.2 logging module . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
16.3 Module of the Week Series . . . . . . . . . . . . . . . . . . . . . . 107
16.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
107
17.1 Passing tuples around . . . . . . . . . . . . . . . . . . . . . . . . 107
17.2 Special Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
17.3 Single Statement Blocks . . . . . . . . . . . . . . . . . . . . . . . 109
17.4 Lambda Forms . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
17.5 List Comprehension . . . . . . . . . . . . . . . . . . . . . . . . . 110
17.6 Receiving Tuples and Dictionaries in Functions . . . . . . . . . . 110
17.7 The assert statement . . . . . . . . . . . . . . . . . . . . . . . . . 111
17.8 Escape Sequences . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
17.8.1 Raw String . . . . . . . . . . . . . . . . . . . . . . . . . . 112
17.9 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
112
18.1 Example Code . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
18.2 Questions and Answers . . . . . . . . . . . . . . . . . . . . . . . . 114
18.3 Tutorials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
18.4 Videos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
18.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
18.6 News . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
18.7 Installing libraries . . . . . . . . . . . . . . . . . . . . . . . . . . 114
18.8 Graphical Software . . . . . . . . . . . . . . . . . . . . . . . . . . 114
18.8.1 Summary of GUI Tools . . . . . . . . . . . . . . . . . . . 115
18.9 Various Implementations . . . . . . . . . . . . . . . . . . . . . . . 115
18.10Functional Programming (for advanced readers) . . . . . . . . . . 116
18.11Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
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118
20.1 Birth of the Book . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
20.2 Teenage Years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
20.3 Now . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
20.4 About The Author . . . . . . . . . . . . . . . . . . . . . . . . . . 119
119
121
22.1 Arabic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
22.2 Brazilian Portuguese . . . . . . . . . . . . . . . . . . . . . . . . . 122
22.3 Catalan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
22.4 Chinese . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
22.5 Chinese Traditional . . . . . . . . . . . . . . . . . . . . . . . . . . 123
22.6 French . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
22.7 German . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
22.8 Greek . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
22.9 Indonesian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
22.10Italian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
22.11Japanese . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
22.12Mongolian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
22.13Norwegian (bokmål) . . . . . . . . . . . . . . . . . . . . . . . . . 126
22.14Polish . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
22.15Portuguese . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
22.16Romanian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
22.17Russian and Ukranian . . . . . . . . . . . . . . . . . . . . . . . . 127
22.18Slovak . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
22.19Spanish . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
22.20Swedish . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
22.21Turkish . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
7
129
1
A Byte of Python
‘A Byte of Python’ is a free book on programming using the Python language.
It serves as a tutorial or guide to the Python language for a beginner audience.
If all you know about computers is how to save text files, then this is the book
for you.
This book is written for the latest Python 3, even though Python 2 is the
commonly found version of Python today (read more about it in
1.1
Who Reads A Byte of Python?
Here are what people are saying about the book:
The best thing i found was “A Byte of Python”, which is simply a
brilliant book for a beginner. It’s well written, the concepts are well
explained with self evident examples.
–
This is the best beginner’s tutorial I’ve ever seen! Thank you for
your effort.
– Walt Michalik (wmich50-at-theramp-dot-net)
You’ve made the best Python tutorial I’ve found on the Net. Great
work. Thanks!
– Joshua Robin (joshrob-at-poczta-dot-onet-dot-pl)
Excellent gentle introduction to programming #Python for beginners
–
8
Hi, I’m from Dominican Republic. My name is Pavel, recently I read
your book ‘A Byte of Python’ and I consider it excellent!! :). I learnt
much from all the examples. Your book is of great help for newbies
like me. . .
– Pavel Simo (pavel-dot-simo-at-gmail-dot-com)
I recently finished reading Byte of Python, and I thought I really
ought to thank you. I was very sad to reach the final pages as I now
have to go back to dull, tedious oreilly or etc. manuals for learning
about python. Anyway, I really appreciate your book.
– Samuel Young (sy-one-three-seven-at-gmail-dot-com)
Dear Swaroop, I am taking a class from an instructor that has no
interest in teaching. We are using Learning Python, second edition,
by O’Reilly. It is not a text for beginner without any programming
knowledge, and an instructor that should be working in another field.
Thank you very much for your book, without it I would be clueless
about Python and programming. Thanks a million, you are able to
‘break the message down’ to a level that beginners can understand
and not everyone can.
– Joseph Duarte (jduarte1-at-cfl-dot-rr-dot-com)
I love your book! It is the greatest Python tutorial ever, and a very
useful reference. Brilliant, a true masterpiece! Keep up the good
work!
– Chris-André Sommerseth
I’m just e-mailing you to thank you for writing Byte of Python online.
I had been attempting Python for a few months prior to stumbling
across your book, and although I made limited success with pyGame,
I never completed a program.
Thanks to your simplification of the categories, Python actually seems
a reachable goal. It seems like I have finally learned the foundations
and I can continue into my real goal, game development.
9
. . .
Once again, thanks VERY much for placing such a structured and
helpful guide to basic programming on the web. It shoved me into
and out of OOP with an understanding where two text books had
failed.
– Matt Gallivan (m-underscore-gallivan12-at-hotmail-dot-com)
I would like to thank you for your book ‘A byte of python’ which i
myself find the best way to learn python. I am a 15 year old i live
in egypt my name is Ahmed. Python was my second programming
language i learn visual basic 6 at school but didn’t enjoy it, however
i really enjoyed learning python. I made the addressbook program
and i was sucessful. i will try to start make more programs and read
python programs (if you could tell me source that would be helpful).
I will also start on learning java and if you can tell me where to find
a tutorial as good as yours for java that would help me a lot. Thanx.
– Ahmed Mohammed (sedo-underscore-91-at-hotmail-dot-com)
A wonderful resource for beginners wanting to learn more about
Python is the 110-page PDF tutorial A Byte of Python by Swaroop C
H. It is well-written, easy to follow, and may be the best introduction
to Python programming available.
– Drew Ames in an article on
published on Linux.com
Yesterday I got through most of Byte of Python on my Nokia N800
and it’s the easiest and most concise introduction to Python I have
yet encountered. Highly recommended as a starting point for learning
Python.
– Jason Delport on his
Byte of Vim and Python by @swaroopch is by far the best works in
technical writing to me. Excellent reads #FeelGoodFactor
– Surendran says in a
10
“Byte of python” best one by far man
(in response to the question “Can anyone suggest a good, inexpensive
resource for learning the basics of Python?”)
– Justin LoveTrue says in a
“The Book Byte of python was very helpful ..Thanks bigtime :)”
–
Always been a fan of A Byte of Python - made for both new and
experienced programmers.
–
Patrick Harrington, in a StackOverflow answer
Even NASA
The book is even used by NASA! It is being used in their
with their Deep Space Network project.
1.2
Academic Courses
This book is/was being used as instructional material in various educational
institutions:
• ‘Principles of Programming Languages’ course at
• ‘Basic Concepts of Computing’ course at
University of California, Davis
• ‘Programming With Python’ course at
• ‘Introduction to Programming’ course at
• ‘Introduction to Application Programming’ course at
• ‘Information Technology Skills for Meteorology’ course at
• ‘Geoprocessing’ course at
• ‘Multi Agent Semantic Web Systems’ course at the
1.3
License
This book is licensed under the
Creative Commons Attribution-Share Alike 3.0
license.
This means:
11
• You are free to Share i.e. to copy, distribute and transmit this book
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Please note:
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and clearly indicating that the original text can be fetched from this
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• All the code/scripts provided in this book is licensed under the
unless otherwise noted.
1.4
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1.5
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1.6
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1.7
Read the book in your native language
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12
2
Preface
Python is probably one of the few programming languages which is both simple
and powerful. This is good for beginners as well as for experts, and more
importantly, is fun to program with. This book aims to help you learn this
wonderful language and show how to get things done quickly and painlessly - in
effect ‘The Perfect Anti-venom to your programming problems’.
2.1
Who This Book Is For
This book serves as a guide or tutorial to the Python programming language. It
is mainly targeted at newbies. It is useful for experienced programmers as well.
The aim is that if all you know about computers is how to save text files, then you
can learn Python from this book. If you have previous programming experience,
then you can also learn Python from this book.
If you do have previous programming experience, you will be interested in the
differences between Python and your favorite programming language - I have
highlighted many such differences. A little warning though, Python is soon going
to become your favorite programming language!
2.2
History Lesson
I first started with Python when I needed to write an installer for software I had
written called ‘Diamond’ so that I could make the installation easy. I had to
choose between Python and Perl bindings for the Qt library. I did some research
on the web and I came across
, a famous and
respected hacker, where he talked about how Python had become his favorite
programming language. I also found out that the PyQt bindings were more
mature compared to Perl-Qt. So, I decided that Python was the language for
me.
Then, I started searching for a good book on Python. I couldn’t find any! I
did find some O’Reilly books but they were either too expensive or were more
like a reference manual than a guide. So, I settled for the documentation that
came with Python. However, it was too brief and small. It did give a good idea
about Python but was not complete. I managed with it since I had previous
programming experience, but it was unsuitable for newbies.
About six months after my first brush with Python, I installed the (then) latest
Red Hat 9.0 Linux and I was playing around with KWord. I got excited about it
and suddenly got the idea of writing some stuff on Python. I started writing a few
pages but it quickly became 30 pages long. Then, I became serious about making
it more useful in a book form. After a lot of rewrites, it has reached a stage
13
where it has become a useful guide to learning the Python language. I consider
this book to be my contribution and tribute to the open source community.
This book started out as my personal notes on Python and I still consider it in
the same way, although I’ve taken a lot of effort to make it more palatable to
others :)
In the true spirit of open source, I have received lots of constructive suggestions,
criticisms and
from enthusiastic readers which has helped me improve
this book a lot.
2.3
Status Of The Book
This book has been reformatted in October 2012 using Pandoc to allow generation
of ebooks as requested by several users, along with errata fixes and updates.
Changes in December 2008 edition (from the earlier major revision in March
2005) was updating for the Python 3.0 release.
The book needs the help of its readers such as yourselves to point out any parts
of the book which are not good, not comprehensible or are simply wrong. Please
or the respective
with your comments and
suggestions.
2.4
Official Website
The official website of the book is
http://www.swaroopch.com/notes/Python
where you can read the whole book online, download the latest versions of the
book,
, and also send me feedback.
2.5
Something To Think About
There are two ways of constructing a software design: one way is to
make it so simple that there are obviously no deficiencies; the other
is to make it so complicated that there are no obvious deficiencies.
– C. A. R. Hoare
Success in life is a matter not so much of talent and opportunity as
of concentration and perseverance.
– C. W. Wendte
14
3
Introduction
Python is one of those rare languages which can claim to be both simple and
powerful
. You will find yourself pleasantly surprised to see how easy it is to
concentrate on the solution to the problem rather than the syntax and structure
of the language you are programming in.
The official introduction to Python is:
Python is an easy to learn, powerful programming language. It
has efficient high-level data structures and a simple but effective
approach to object-oriented programming. Python’s elegant syntax
and dynamic typing, together with its interpreted nature, make it
an ideal language for scripting and rapid application development in
many areas on most platforms.
I will discuss most of these features in more detail in the next section.
Story behind the name
Guido van Rossum, the creator of the Python lan-
guage, named the language after the BBC show “Monty Python’s Flying
Circus”. He doesn’t particularly like snakes that kill animals for food by
winding their long bodies around them and crushing them.
3.1
Features of Python
3.1.1
Simple
Python is a simple and minimalistic language. Reading a good Python program
feels almost like reading English, although very strict English! This pseudo-code
nature of Python is one of its greatest strengths. It allows you to concentrate on
the solution to the problem rather than the language itself.
3.1.2
Easy to Learn
As you will see, Python is extremely easy to get started with. Python has an
extraordinarily simple syntax, as already mentioned.
3.1.3
Free and Open Source
Python is an example of a FLOSS (Free/Libré and Open Source Software). In
simple terms, you can freely distribute copies of this software, read its source
code, make changes to it, and use pieces of it in new free programs. FLOSS is
based on the concept of a community which shares knowledge. This is one of the
reasons why Python is so good - it has been created and is constantly improved
by a community who just want to see a better Python.
15
3.1.4
High-level Language
When you write programs in Python, you never need to bother about the
low-level details such as managing the memory used by your program, etc.
3.1.5
Portable
Due to its open-source nature, Python has been ported to (i.e. changed to make
it work on) many platforms. All your Python programs can work on any of these
platforms without requiring any changes at all if you are careful enough to avoid
any system-dependent features.
You can use Python on Linux, Windows, FreeBSD, Macintosh, Solaris, OS/2,
Amiga, AROS, AS/400, BeOS, OS/390, z/OS, Palm OS, QNX, VMS, Psion,
Acorn RISC OS, VxWorks, PlayStation, Sharp Zaurus, Windows CE and even
PocketPC!
You can even use a platform like
to create games for iOS (iPhone, iPad)
and Android.
3.1.6
Interpreted
This requires a bit of explanation.
A program written in a compiled language like C or C++ is converted from the
source language i.e. C or C++ into a language that is spoken by your computer
(binary code i.e. 0s and 1s) using a compiler with various flags and options.
When you run the program, the linker/loader software copies the program from
hard disk to memory and starts running it.
Python, on the other hand, does not need compilation to binary. You just run
the program directly from the source code. Internally, Python converts the
source code into an intermediate form called bytecodes and then translates this
into the native language of your computer and then runs it. All this, actually,
makes using Python much easier since you don’t have to worry about compiling
the program, making sure that the proper libraries are linked and loaded, etc.
This also makes your Python programs much more portable, since you can just
copy your Python program onto another computer and it just works!
3.1.7
Object Oriented
Python supports procedure-oriented programming as well as object-oriented
programming. In procedure-oriented languages, the program is built around
procedures or functions which are nothing but reusable pieces of programs. In
object-oriented
languages, the program is built around objects which combine
16
data and functionality. Python has a very powerful but simplistic way of doing
OOP, especially when compared to big languages like C++ or Java.
3.1.8
Extensible
If you need a critical piece of code to run very fast or want to have some piece
of algorithm not to be open, you can code that part of your program in C or
C++ and then use it from your Python program.
3.1.9
Embeddable
You can embed Python within your C/C++ programs to give ‘scripting’ capa-
bilities for your program’s users.
3.1.10
Extensive Libraries
The Python Standard Library is huge indeed. It can help you do various things
involving regular expressions,documentation generation, unit testing, threading,
databases, web browsers, CGI, FTP, email, XML, XML-RPC, HTML, WAV
files, cryptography, GUI (graphical user interfaces), and other system-dependent
stuff. Remember, all this is always available wherever Python is installed. This
is called the Batteries Included philosophy of Python.
Besides the standard library, there are various other high-quality libraries which
you can find at the
Summary
Python is indeed an exciting and powerful language. It has the right
combination of performance and features that make writing programs in
Python both fun and easy.
3.2
Python 2 versus 3
You can ignore this section if you’re not interested in the difference between
Python 2 and Python 3. But please do be aware of which version you are using.
This book was rewritten in 2008 for Python 3. It was one of the first books to
use Python 3. This, unfortunately, resulted in confusion for readers who would
try to use Python 2 with the Python 3 version of the book and vice-versa. But
slowly, the world is still migrating to Python 3.
So, yes, you will be learning to use Python 3 in this book, even if you want
to ultimately use Python 2. Remember that once you have properly understood
and learn to use either of them, you can easily learn the changes between the
two versions and adapt easily. The hard part is learning programming and
17
understanding the core Python language itself. That is our goal in this book,
and once you have achieved that goal, you can easily use Python 2 or Python 3
depending on your situation.
For details on differences between Python 2 to Python 3, see the
3.3
What Programmers Say
You may find it interesting to read what great hackers like ESR have to say
about Python:
(1) Eric S. Raymond is the author of “The Cathedral and the Bazaar” and is
also the person who coined the term Open Source. He says that
has become his favorite programming language
. This article was the real
inspiration for my first brush with Python.
(2) Bruce Eckel is the author of the famous Thinking in Java and Thinking in
C++
books. He says that no language has made him more productive than
Python. He says that Python is perhaps the only language that focuses on
making things easier for the programmer. Read the
for
more details.
(3) Peter Norvig is a well-known Lisp author and Director of Search Quality
at Google (thanks to Guido van Rossum for pointing that out). He says
that Python has always been an integral part of Google. You can actually
verify this statement by looking at the
page which lists Python
knowledge as a requirement for software engineers.
4
Installation
4.1
Installation on Windows
Visit
http://www.python.org/download/
and download the latest version. The
installation is just like any other Windows-based software.
Caution
When you are given the option of unchecking any “optional” compo-
nents, don’t uncheck any.
4.1.1
DOS Prompt
If you want to be able to use Python from the Windows command line i.e. the
DOS prompt, then you need to set the PATH variable appropriately.
18
For Windows 2000, XP, 2003 , click on Control Panel — System — Advanced
— Environment Variables. Click on the variable named PATH in the ‘System
Variables’ section, then select Edit and add ;C:\Python33 (please verify that
this folder exists, it will be different for newer versions of Python) to the end of
what is already there. Of course, use the appropriate directory name.
For older versions of Windows, open the file C:\AUTOEXEC.BAT and add the line
‘PATH=%PATH%;C:\Python33’ (without the quotes) and restart the system. For
Windows NT, use the AUTOEXEC.NT file.
For Windows Vista:
1. Click Start and choose Control Panel
2. Click System, on the right you’ll see “View basic information about your
computer”
3. On the left is a list of tasks, the last of which is “Advanced system settings.”
Click that.
4. The Advanced tab of the System Properties dialog box is shown. Click the
Environment Variables button on the bottom right.
5. In the lower box titled “System Variables” scroll down to Path and click
the Edit button.
6. Change your path as need be.
7. Restart your system. Vista didn’t pick up the system path environment
variable change until I restarted.
For Windows 7:
1. Right click on Computer from your desktop and select properties or Click
Start and choose Control Panel — System and Security — System. Click
on Advanced system settings on the left and then click on the Advanced
tab. At the bottom click on Environment Variables and under System
variables, look for the PATH variable, select and then press Edit.
2. Go to the end of the line under Variable value and append ;C:\Python33.
3. If the value was %SystemRoot%\system32; It will now become
%SystemRoot%\system32;C:\Python33
4. Click ok and you are done. No restart is required.
4.1.2
Running Python prompt on Windows
For Windows users, you can run the interpreter in the command line if you have
set the PATH variable appropriately
To open the terminal in Windows, click the start button and click ‘Run’. In the
dialog box, type cmd and press enter key.
Then, type python3 -V and ensure there are no errors.
19
4.2
Installation on Mac OS X
For Mac OS X users, open the terminal by pressing Command+Space keys (to
open Spotlight search), type Terminal and press enter key.
Install
by running:
ruby -e "$(curl -fsSkL raw.github.com/mxcl/homebrew/go)"
Then install Python 3 using:
brew install python3
Now, run python3 -V and ensure there are no errors.
4.3
Installation on Linux
For Linux users, open the terminal by opening the Terminal application or by
pressing Alt + F2 and entering gnome-terminal. If that doesn’t work, please
refer the documentation or forums of your particular Linux distribution.
Next, we have to install the python3 package. For example, on Ubuntu, you
can use
. Please check the documentation or
forums of the Linux distribution that you have installed for the correct package
manager command to run.
Once you have finished the installation, run the python3 -V command in a shell
and you should see the version of Python on the screen:
$ python3 -V
Python 3.3.0
Note
$ is the prompt of the shell. It will be different for you depending on the
settings of the operating system on your computer, hence I will indicate
the prompt by just the $ symbol.
Default in new versions of your distribution?
Newer distributions such
as
Ubuntu 12.10 are making Python 3 the default version
, so check if it is
already installed.
4.4
Summary
From now on, we will assume that you have Python 3 installed on your system.
Next, we will write our first Python 3 program.
20
5
First Steps
We will now see how to run a traditional ‘Hello World’ program in Python. This
will teach you how to write, save and run Python programs.
There are two ways of using Python to run your program - using the interactive
interpreter prompt or using a source file. We will now see how to use both of
these methods.
5.1
Using The Interpreter Prompt
Open the terminal in your operating system (as discussed previously in the
) and then open the Python prompt by typing python3 and
pressing enter key.
Once you have started python3, you should see >>> where you can start typing
stuff. This is called the Python interpreter prompt.
At the Python interpreter prompt, type print(’Hello World’) followed by the
enter key. You should see the words Hello World as output.
Here is an example of what you should be seeing, when using a Mac OS X
computer. The details about the Python software will differ based on your
computer, but the part from the prompt (i.e. from >>> onwards) should be the
same regardless of the operating system.
$ python3
Python 3.3.0 (default, Oct 22 2012, 12:20:36)
[GCC 4.2.1 Compatible Apple Clang 4.0 ((tags/Apple/clang-421.0.60))] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> print('hello world')
hello world
>>>
Notice that Python gives you the output of the line immediately! What you just
entered is a single Python statement. We use print to (unsurprisingly) print
any value that you supply to it. Here, we are supplying the text Hello World
and this is promptly printed to the screen.
How to Quit the Interpreter Prompt
If you are using a Linux or Unix
shell, you can exit the interpreter prompt by pressing ctrl-d or entering
exit() (note: remember to include the parentheses, ‘()’) followed by the
enter key. If you are using the Windows command prompt, press ctrl-z
followed by the enter key.
21
5.2
Choosing An Editor
We cannot type out our program at the interpreter prompt every time we want
to run something, so we have to save them in files and can run our programs
any number of times.
To create our Python source files, we need an editor software where you can type
and save. A good programmer’s editor will make your life easier in writing the
source files. Hence, the choice of an editor is crucial indeed. You have to choose
an editor as you would choose a car you would buy. A good editor will help you
write Python programs easily, making your journey more comfortable and helps
you reach your destination (achieve your goal) in a much faster and safer way.
One of the very basic requirements is syntax highlighting where all the different
parts of your Python program are colorized so that you can see your program
and visualize its running.
If you have no idea where to start, I would recommend using
software which is available on Windows, Mac OS X and Linux.
If you are using Windows, do not use Notepad - it is a bad choice because
it does not do syntax highlighting and also importantly it does not support
indentation of the text which is very important in our case as we will see later.
Good editors such as Komodo Edit will automatically do this.
If you are an experienced programmer, then you must be already using
or
. Needless to say, these are two of the most powerful editors and you
will benefit from using them to write your Python programs. I personally use
both for most of my programs, and have even written an
In case you are willing to take the time to learn Vim or Emacs, then I highly
recommend that you do learn to use either of them as it will be very useful for
you in the long run. However, as I mentioned before, beginners can start with
Komodo Edit and focus the learning on Python rather than the editor at this
moment.
To reiterate, please choose a proper editor - it can make writing Python programs
more fun and easy.
For Vim users
There is a good introduction on how to
. Also recommended is the
and my
For Emacs users
There is a good introduction on how to
erful Python IDE by Pedro Kroger
. Also recommended is
22
5.3
Using A Source File
Now let’s get back to programming. There is a tradition that whenever you
learn a new programming language, the first program that you write and run is
the ‘Hello World’ program - all it does is just say ‘Hello World’ when you run it.
As Simon Cozens (the author of the amazing ‘Beginning Perl’ book) puts it, it
is the “traditional incantation to the programming gods to help you learn the
language better.”
Start your choice of editor, enter the following program and save it as hello.py.
If you are using Komodo Edit, click on File — New — New File, type the lines:
(
'Hello World'
)
In Komodo Edit, do File — Save to save to a file.
Where should you save the file? To any folder for which you know the location
of the folder. If you don’t understand what that means, create a new folder and
use that location to save and run all your Python programs:
• C:\\py on Windows
• /tmp/py on Linux
• /tmp/py on Mac OS X
To create a folder, use the mkdir command in the terminal, for example, mkdir
/tmp/py.
Important
Always ensure that you give it the file extension of .py, for example,
foo.py.
In Komodo Edit, click on Tools — Run Command, type python3 hello.py and
click on Run and you should see the output printed like in the screenshot below.
The best way, though, is to type it in Komodo Edit but to use a terminal:
1. Open a terminal as explained in the
2. Change directory where you saved the file, for example, cd /tmp/py
3. Run the program by entering the command python3 hello.py.
The output is as shown below.
$ python3 hello.py
Hello World
23
Figure 1: Screenshot of Komodo Edit with the Hello World program
24
If you got the output as shown above, congratulations! - you have successfully
run your first Python program. You have successfully crossed the hardest part
of learning programming, which is, getting started with your first program!
In case you got an error, please type the above program exactly as shown above
and run the program again. Note that Python is case-sensitive i.e. print is not
the same as Print - note the lowercase p in the former and the uppercase P in
the latter. Also, ensure there are no spaces or tabs before the first character in
each line - we will
see why this is important later
How It Works
A Python program is composed of statements. In our first program, we have
only one statement. In this statement, we call the print function which just
prints the text ’Hello World’. We will learn about functions in detail in a
- what you should understand now is that whatever you supply in the
parentheses will be printed back to the screen. In this case, we supply the text
’Hello World’.
5.3.1
Executable Python Programs
This applies only to Linux and Unix users but Windows users should know this
as well.
Every time, you want to run a Python program, we have to explicitly call
python3 foo.py, but why can’t we run it just like any other program on our
computer? We can achieve that by using something called the hashbang line.
Add the below line as the first line of your program:
#!/usr/bin/env python3
So, your program should look like this now:
#!/usr/bin/env python3
(
'Hello World'
)
Second, we have to give the program executable permission using the chmod
command then run the source program.
The chmod command is used here to change the mode of the file by giving
execute permission to all users of the system.
$ chmod a+x hello.py
Now, we can run our program directly because our operating system calls
/usr/bin/env which in turn will find our Python 3 software and hence knows
how to run our source file:
25
$ ./hello.py
Hello World
We use the ./ to indicate that the program is located in the current folder.
To make things more fun, you can rename the file to just hello and run it as
./hello and it will still work since the system knows that it has to run the
program using the interpreter whose location is specified in the first line in the
source file.
So far, we have been able to run our program as long as we know the exact
path. What if we wanted to be able to run the program from folder? You can do
this by storing the program in one of the folders listed in the PATH environment
variable.
Whenever you run any program, the system looks for that program in each of
the folders listed in the PATH environment variable and then runs that program.
We can make this program available everywhere by simply copying this source
file to one of the directories listed in PATH.
$ echo $PATH
/usr/local/bin:/usr/bin:/bin:/usr/X11R6/bin:/home/swaroop/bin
$ cp hello.py /home/swaroop/bin/hello
$ hello
Hello World
We can display the PATH variable using the echo command and prefixing the
variable name by $ to indicate to the shell that we need the value of this
“environment variable”. We see that /home/swaroop/bin is one of the directories
in the PATH variable where swaroop is the username I am using in my system.
There will usually be a similar directory for your username on your system.
If you want to add a directory of your choice to the PATH variable - this
can be done by running export PATH=$PATH:/home/swaroop/mydir where
’/home/swaroop/mydir’ is the directory I want to add to the PATH variable.
This method is very useful if you want to write commands you can run anytime,
anywhere. It is like creating your own commands just like cd or any other
commands that you use in the terminal.
5.4
Getting Help
If you need quick information about any function or statement in Python, then
you can use the built-in help functionality. This is very useful especially when
using the interpreter prompt. For example, run help(print) - this displays the
help for the print function which is used to print things to the screen.
26
Note
Press q to exit the help.
Similarly, you can obtain information about almost anything in Python. Use
help() to learn more about using help itself!
In case you need to get help for operators like return, then you need to put
those inside quotes such as help(’return’) so that Python doesn’t get confused
on what we’re trying to do.
5.5
Summary
You should now be able to write, save and run Python programs at ease.
Now that you are a Python user, let’s learn some more Python concepts.
6
Basics
Just printing ‘Hello World’ is not enough, is it? You want to do more than that
- you want to take some input, manipulate it and get something out of it. We
can achieve this in Python using constants and variables, and we’ll learn some
other concepts as well in this chapter.
6.1
Comments
Comments
are any text to the right of the # symbol and is mainly useful as notes
for the reader of the program.
For example:
(
'Hello World'
)
# Note that print is a function
or:
# Note that print is a function
(
'Hello World'
)
Use as many useful comments as you can in your program to:
• explain assumptions
• explain important decisions
• explain important details
• explain problems you’re trying to solve
27
• explain problems you’re trying to overcome in your program, etc.
Code tells you how, comments should tell you why.
This is useful for readers of your program so that they can easily understand
what the program is doing. Remember, that person can be yourself after six
months!
6.2
Literal Constants
An example of a literal constant is a number like 5, 1.23, or a string like ’This
is a string’or "It’s a string!". It is called a literal because it is literal -
you use its value literally. The number 2 always represents itself and nothing
else - it is a constant because its value cannot be changed. Hence, all these are
referred to as literal constants.
6.3
Numbers
Numbers are mainly of two types - integers and floats.
An examples of an integer is 2 which is just a whole number.
Examples of floating point numbers (or floats for short) are 3.23 and 52.3E-4.
The E notation indicates powers of 10. In this case, 52.3E-4 means 52.3 *
10ˆ-4ˆ.
Note for Experienced Programmers
There is no separate long type. The
int type can be an integer of any size.
6.4
Strings
A string is a sequence of characters. Strings are basically just a bunch of words.
You will be using strings in almost every Python program that you write, so pay
attention to the following part.
6.4.1
Single Quote
You can specify strings using single quotes such as ’Quote me on this’. All
white space i.e. spaces and tabs are preserved as-is.
6.4.2
Double Quotes
Strings in double quotes work exactly the same way as strings in single quotes.
An example is "What’s your name?"
28
6.4.3
Triple Quotes
You can specify multi-line strings using triple quotes - (""" or ”’). You can use
single quotes and double quotes freely within the triple quotes. An example is:
'''This is a multi-line string. This is the first line.
This is the second line.
"What's your name?," I asked.
He said "Bond, James Bond."
'''
6.4.4
Strings Are Immutable
This means that once you have created a string, you cannot change it. Although
this might seem like a bad thing, it really isn’t. We will see why this is not a
limitation in the various programs that we see later on.
Note for C/C++ Programmers
There is no separate char data type in
Python. There is no real need for it and I am sure you won’t miss it.
Note for Perl/PHP Programmers
Remember that single-quoted strings
and double-quoted strings are the same - they do not differ in any way.
6.4.5
The format method
Sometimes we may want to construct strings from other information. This is
where the format() method is useful.
Save the following lines as a file str_format.py:
age =
20
name =
'Swaroop'
(
'{0} was {1} years old when he wrote this book'
.
format
(name, age))
(
'Why is {0} playing with that python?'
.
format
(name))
Output:
$ python3 str_format.py
Swaroop was 20 years old when he wrote this book
Why is Swaroop playing with that python?
29
How It Works:
A string can use certain specifications and subsequently, the format method can
be called to substitute those specifications with corresponding arguments to the
format method.
Observe the first usage where we use {0} and this corresponds to the variable
name which is the first argument to the format method. Similarly, the second
specification is {1} corresponding to age which is the second argument to the
format method. Note that Python starts counting from 0 which means that first
position is at index 0, second position is at index 1, and so on.
Notice that we could have achieved the same using string concatenation: name +
’ is ’ + str(age) + ’ years old’ but that is much uglier and error-prone.
Second, the conversion to string would be done automatically by the format
method instead of the explicit conversion to strings needed in this case. Third,
when using the format method, we can change the message without having to
deal with the variables used and vice-versa.
Also note that the numbers are optional, so you could have also written as:
age =
20
name =
'Swaroop'
(
'{} was {} years old when he wrote this book'
.
format
(name, age))
(
'Why is {} playing with that python?'
.
format
(name))
which will give the same exact output as the previous program.
What Python does in the format method is that it substitutes each argument
value into the place of the specification. There can be more detailed specifications
such as:
decimal (.) precision of
3
for
float
'0.333'
>>>
'{0:.3}'
.
format
(
1
/
3
)
fill
with
underscores (_)
with
the text centered
(^) to
11
width
'___hello___'
>>>
'{0:_^11}'
.
format
(
'hello'
)
keyword-based
'Swaroop wrote A Byte of Python'
>>>
'{name} wrote {book}'
.
format
(name=
'Swaroop'
, book=
'A Byte of Python'
)
6.5
Variable
Using just literal constants can soon become boring - we need some way of
storing any information and manipulate them as well. This is where variables
come into the picture. Variables are exactly what the name implies - their value
can vary, i.e., you can store anything using a variable. Variables are just parts
30
of your computer’s memory where you store some information. Unlike literal
constants, you need some method of accessing these variables and hence you
give them names.
6.6
Identifier Naming
Variables are examples of identifiers. Identifiers are names given to identify
something
. There are some rules you have to follow for naming identifiers:
• The first character of the identifier must be a letter of the alphabet (up-
percase ASCII or lowercase ASCII or Unicode character) or an underscore
(‘_’).
• The rest of the identifier name can consist of letters (uppercase ASCII or
lowercase ASCII or Unicode character), underscores (‘_’) or digits (0-9).
• Identifier names are case-sensitive. For example, myname and myName are
not
the same. Note the lowercase n in the former and the uppercase N in
the latter.
• Examples of valid identifier names are i, __my_name, name_23. Examples
of ‘’invalid” identifier names are 2things, this is spaced out, my-name,
>a1b2_c3 and "this_is_in_quotes".
6.7
Data Types
Variables can hold values of different types called data types. The basic types
are numbers and strings, which we have already discussed. In later chapters, we
will see how to create our own types using
6.8
Object
Remember, Python refers to anything used in a program as an object. This is
meant in the generic sense. Instead of saying ‘the something’, we say ‘the object’.
Note for Object Oriented Programming users
Python is strongly object-
oriented in the sense that everything is an object including numbers, strings
and functions.
We will now see how to use variables along with literal constants. Save the
following example and run the program.
31
6.9
How to write Python programs
Henceforth, the standard procedure to save and run a Python program is as
follows:
1. Open your editor of choice, such as Komodo Edit.
2. Type the program code given in the example.
3. Save it as a file with the filename mentioned.
4. Run the interpreter with the command python3 program.py to run the
program.
6.10
Example: Using Variables And Literal Constants
Filename : var.py
i =
5
(i)
i = i +
1
(i)
s =
'''This is a multi-line string.
This is the second line.'''
(s)
Output:
$ python3 var.py
5
6
This is a multi-line string.
This is the second line.
How It Works:
Here’s how this program works. First, we assign the literal constant value 5 to
the variable i using the assignment operator (=). This line is called a statement
because it states that something should be done and in this case, we connect the
variable name i to the value 5. Next, we print the value of i using the print
function which, unsurprisingly, just prints the value of the variable to the screen.
Then we add 1 to the value stored in i and store it back. We then print it and
expectedly, we get the value 6.
Similarly, we assign the literal string to the variable s and then print it.
Note for static language programmers
Variables are used by just assigning
them a value. No declaration or data type definition is needed/used.
32
6.10.1
Logical And Physical Line
A physical line is what you see when you write the program. A logical line is
what Python sees as a single statement. Python implicitly assumes that each
physical line
corresponds to a logical line.
An example of a logical line is a statement like print(’Hello World’) - if this
was on a line by itself (as you see it in an editor), then this also corresponds to
a physical line.
Implicitly, Python encourages the use of a single statement per line which makes
code more readable.
If you want to specify more than one logical line on a single physical line, then
you have to explicitly specify this using a semicolon (;) which indicates the end
of a logical line/statement. For example,
i =
5
(i)
is effectively same as
i =
5
;
(i);
and the same can be written as
i =
5
;
(i);
or even
i =
5
;
(i)
However, I strongly recommend that you stick to writing a maximum of a
single logical line on each single physical line
. The idea is that you should
never use the semicolon. In fact, I have never used or even seen a semicolon in a
Python program.
There is one kind of situation where this concept is really useful : if you have
a long line of code, you can break it into multiple physical lines by using the
backslash. This is referred to as explicit line joining:
s =
'This is a string. \
This continues the string.'
(s)
33
This gives the output:
This is a string. This continues the string.
Similarly,
\
(i)
is the same as
(i)
Sometimes, there is an implicit assumption where you don’t need to use a
backslash. This is the case where the logical line has a starting parentheses,
starting square brackets or a starting curly braces but not an ending one. This is
called implicit line joining. You can see this in action when we write programs
using
in later chapters.
6.10.2
Indentation
Whitespace is important in Python. Actually, whitespace at the beginning
of the line is important
. This is called indentation. Leading whitespace
(spaces and tabs) at the beginning of the logical line is used to determine the
indentation level of the logical line, which in turn is used to determine the
grouping of statements.
This means that statements which go together must have the same indentation.
Each such set of statements is called a block. We will see examples of how
blocks are important in later chapters.
One thing you should remember is that wrong indentation can give rise to errors.
For example:
i =
5
(
'Value is '
, i)
# Error! Notice a single space at the start of the line
(
'I repeat, the value is '
, i)
When you run this, you get the following error:
File "whitespace.py", line 4
print('Value is ', i) # Error! Notice a single space at the start of the line
^
IndentationError: unexpected indent
34
Notice that there is a single space at the beginning of the second line. The error
indicated by Python tells us that the syntax of the program is invalid i.e. the
program was not properly written. What this means to you is that you cannot
arbitrarily start new blocks of statements
(except for the default main block
which you have been using all along, of course). Cases where you can use new
blocks will be detailed in later chapters such as the
How to indent
Use only spaces for indentation, with a tab stop of 4 spaces.
Good editors like Komodo Edit will automatically do this for you. Make
sure you use a consistent number of spaces for indentation, otherwise your
program will show errors.
Note to static language programmers
Python will always use indentation
for blocks and will never use braces. Run from __future__ import
braces to learn more.
6.11
Summary
Now that we have gone through many nitty-gritty details, we can move on
to more interesting stuff such as control flow statements. Be sure to become
comfortable with what you have read in this chapter.
7
Operators and Expressions
Most statements (logical lines) that you write will contain expressions. A simple
example of an expression is 2 + 3. An expression can be broken down into
operators and operands.
Operators
are functionality that do something and can be represented by symbols
such as + or by special keywords. Operators require some data to operate on
and such data is called operands. In this case, 2 and 3 are the operands.
7.1
Operators
We will briefly take a look at the operators and their usage:
Note that you can evaluate the expressions given in the examples using the
interpreter interactively. For example, to test the expression 2 + 3, use the
interactive Python interpreter prompt:
>>>
2
+
3
5
>>>
3
*
5
35
15
>>>
+ (plus)
Adds two objects
3 + 5 gives 8. ’a’ + ’b’ gives ’ab’.
- (minus)
Gives the subtraction of one number from the other; if the first
operand is absent it is assumed to be zero.
-5.2 gives a negative number and 50 - 24 gives 26.
* (multiply)
Gives the multiplication of the two numbers or returns the string
repeated that many times.
2 * 3 gives 6. ’la’ * 3 gives ’lalala’.
** (power)
Returns x to the power of y
3 ** 4 gives 81 (i.e. 3 * 3 * 3 * 3)
/ (divide)
Divide x by y
4 / 3 gives 1.3333333333333333.
// (floor division)
Returns the floor of the quotient
4 // 3 gives 1.
% (modulo)
Returns the remainder of the division
8 % 3 gives 2. -25.5 % 2.25 gives 1.5.
<< (left shift)
Shifts the bits of the number to the left by the number of bits
specified. (Each number is represented in memory by bits or binary digits
i.e. 0 and 1)
2 << 2 gives 8. 2 is represented by 10 in bits.
Left shifting by 2 bits gives 1000 which represents the decimal 8.
>> (right shift)
Shifts the bits of the number to the right by the number of
bits specified.
11 >> 1 gives 5.
11 is represented in bits by 1011 which when right shifted by 1 bit gives
101which is the decimal 5.
& (bit-wise AND)
Bit-wise AND of the numbers
5 & 3 gives 1.
| (bit-wise OR)
Bitwise OR of the numbers
5 | 3 gives 7
36
ˆ (bit-wise XOR)
Bitwise XOR of the numbers
5 ˆ 3 gives 6
~ (bit-wise invert)
The bit-wise inversion of x is -(x+1)
~5 gives -6.
< (less than)
Returns whether x is less than y. All comparison operators return
True or False. Note the capitalization of these names.
5 < 3 gives False and 3 < 5 gives True.
Comparisons can be chained arbitrarily: 3 < 5 < 7 gives True.
> (greater than)
Returns whether x is greater than y
5 > 3 returns True. If both operands are numbers, they are first
converted to a common type. Otherwise, it always returns False.
<= (less than or equal to)
Returns whether x is less than or equal to y
x = 3; y = 6; x <= y returns True.
>= (greater than or equal to)
Returns whether x is greater than or equal to
y
x = 4; y = 3; x >= 3 returns True.
== (equal to)
Compares if the objects are equal
x = 2; y = 2; x == y returns True.
x = ’str’; y = ’stR’; x == y returns False.
x = ’str’; y = ’str’; x == y returns True.
!= (not equal to)
Compares if the objects are not equal
x = 2; y = 3; x != y returns True.
not (boolean NOT)
If x is True, it returns False. If x is False, it returns
True.
x = True; not x returns False.
and (boolean AND)
x and y returns False if x is False, else it returns
evaluation of y
x = False; y = True; x and y returns False since x is False. In this
case, Python will not evaluate y since it knows that the left hand side
of the ‘and’ expression is False which implies that the whole expression
will be False irrespective of the other values. This is called short-circuit
evaluation.
or (boolean OR)
If x is True, it returns True, else it returns evaluation of y
x = True; y = False; x or y returns True. Short-circuit evaluation
applies here as well.
37
7.1.1
Shortcut for math operation and assignment
It is common to run a math operation on a variable and then assign the result of
the operation back to the variable, hence there is a shortcut for such expressions:
You can write:
a =
2
a = a *
3
as:
a =
2
a *=
3
Notice that var = var operation expression becomes var operation=
expression.
7.2
Evaluation Order
If you had an expression such as 2 + 3 * 4, is the addition done first or the
multiplication? Our high school maths tells us that the multiplication should be
done first. This means that the multiplication operator has higher precedence
than the addition operator.
The following table gives the precedence table for Python, from the lowest
precedence (least binding) to the highest precedence (most binding). This
means that in a given expression, Python will first evaluate the operators and
expressions lower in the table before the ones listed higher in the table.
The following table, taken from the
, is provided for
the sake of completeness. It is far better to use parentheses to group operators
and operands appropriately in order to explicitly specify the precedence. This
makes the program more readable. See
Changing the Order of Evaluation
below
for details.
lambda
Lambda Expression
or
Boolean OR
and
Boolean AND
not x
Boolean NOT
in, not in
Membership tests
is, is not
Identity tests
38
<, <=, >, >=, !=, ==
Comparisons
|
Bitwise OR
ˆ
Bitwise XOR
&
Bitwise AND
<<, >>
Shifts
+, -
Addition and subtraction
*, /, //, %
Multiplication, Division, Floor Division and Remainder
+x, -x
Positive, Negative
~x
Bitwise NOT
**
Exponentiation
x.attribute
Attribute reference
x[index]
Subscription
x[index1:index2]
Slicing
f(arguments ...)
Function call
(expressions, ...)
Binding or tuple display
[expressions, ...]
List display
{key:datum, ...}
Dictionary display
The operators which we have not already come across will be explained in later
chapters.
Operators with the same precedence are listed in the same row in the above
table. For example, + and - have the same precedence.
7.3
Changing the Order Of Evaluation
To make the expressions more readable, we can use parentheses. For example,
2 + (3 * 4) is definitely easier to understand than 2 + 3 * 4 which requires
knowledge of the operator precedences. As with everything else, the parentheses
should be used reasonably (do not overdo it) and should not be redundant, as in
(2 + (3 * 4)).
There is an additional advantage to using parentheses - it helps us to change the
order of evaluation. For example, if you want addition to be evaluated before
multiplication in an expression, then you can write something like (2 + 3) * 4.
39
7.4
Associativity
Operators are usually associated from left to right. This means that operators
with the same precedence are evaluated in a left to right manner. For example, 2
+ 3 + 4 is evaluated as (2 + 3) + 4. Some operators like assignment operators
have right to left associativity i.e. a = b = c is treated as a = (b = c).
7.5
Expressions
Example (save as expression.py):
length =
5
breadth =
2
area = length * breadth
(
'Area is'
, area)
(
'Perimeter is'
,
2
* (length + breadth))
Output:
$ python3 expression.py
Area is 10
Perimeter is 14
How It Works:
The length and breadth of the rectangle are stored in variables by the same
name. We use these to calculate the area and perimeter of the rectangle with the
help of expressions. We store the result of the expression length * breadth
in the variable area and then print it using the print function. In the second
case, we directly use the value of the expression 2 * (length + breadth) in
the print function.
Also, notice how Python ‘pretty-prints’ the output. Even though we have not
specified a space between ’Area is’ and the variable area, Python puts it for
us so that we get a clean nice output and the program is much more readable
this way (since we don’t need to worry about spacing in the strings we use for
output). This is an example of how Python makes life easy for the programmer.
7.6
Summary
We have seen how to use operators, operands and expressions - these are the
basic building blocks of any program. Next, we will see how to make use of these
in our programs using statements.
40
8
Control Flow
In the programs we have seen till now, there has always been a series of statements
faithfully executed by Python in exact top-down order. What if you wanted to
change the flow of how it works? For example, you want the program to take
some decisions and do different things depending on different situations, such as
printing ‘Good Morning’ or ‘Good Evening’ depending on the time of the day?
As you might have guessed, this is achieved using control flow statements. There
are three control flow statements in Python - if, for and while.
8.1
The if statement
The if statement is used to check a condition: if the condition is true, we
run a block of statements (called the if-block), else we process another block of
statements (called the else-block). The else clause is optional.
Example (save as if.py):
number =
23
guess =
int
(
input
(
'Enter an integer : '
))
if
guess == number:
(
'Congratulations, you guessed it.'
)
# New block starts here
(
'(but you do not win any prizes!)'
)
# New block ends here
elif
guess < number:
(
'No, it is a little higher than that'
)
# Another block
# You can do whatever you want in a block ...
else
:
(
'No, it is a little lower than that'
)
# you must have guessed > number to reach here
(
'Done'
)
# This last statement is always executed, after the if statement is executed
Output:
$ python3 if.py
Enter an integer : 50
No, it is a little lower than that
Done
$ python3 if.py
Enter an integer : 22
No, it is a little higher than that
41
Done
$ python3 if.py
Enter an integer : 23
Congratulations, you guessed it.
(but you do not win any prizes!)
Done
How It Works:
In this program, we take guesses from the user and check if it is the number that
we have. We set the variable number to any integer we want, say 23. Then, we
take the user’s guess using the input() function. Functions are just reusable
pieces of programs. We’ll read more about them in the
We supply a string to the built-in input function which prints it to the screen
and waits for input from the user. Once we enter something and press enter key,
the input() function returns what we entered, as a string. We then convert this
string to an integer using int and then store it in the variable guess. Actually,
the int is a class but all you need to know right now is that you can use it to
convert a string to an integer (assuming the string contains a valid integer in
the text).
Next, we compare the guess of the user with the number we have chosen. If they
are equal, we print a success message. Notice that we use indentation levels to
tell Python which statements belong to which block. This is why indentation is
so important in Python. I hope you are sticking to the “consistent indentation”
rule. Are you?
Notice how the if statement contains a colon at the end - we are indicating to
Python that a block of statements follows.
Then, we check if the guess is less than the number, and if so, we inform the user
that they must guess a little higher than that. What we have used here is the
elif clause which actually combines two related if else-if else statements
into one combined if-elif-else statement. This makes the program easier
and reduces the amount of indentation required.
The elif and else statements must also have a colon at the end of the logical
line followed by their corresponding block of statements (with proper indentation,
of course)
You can have another if statement inside the if-block of an if statement and
so on - this is called a nested if statement.
Remember that the elif and else parts are optional. A minimal valid if
statement is:
if
True
:
(
'Yes, it is true'
)
42
After Python has finished executing the complete if statement along with the
associated elif and else clauses, it moves on to the next statement in the block
containing the if statement. In this case, it is the main block (where execution
of the program starts), and the next statement is the print(’Done’) statement.
After this, Python sees the ends of the program and simply finishes up.
Even though this is a very simple program, I have been pointing out a lot
of things that you should notice. All these are pretty straightforward (and
surprisingly simple for those of you from C/C++ backgrounds). You will need
to become aware of all these things initially, but after some practice you will
become comfortable with them, and it will all feel ‘natural’ to you.
Note for C/C++ Programmers
There is no switch statement in Python.
You can use an if..elif..else statement to do the same thing (and in
some cases, use a
to do it quickly)
8.2
The while Statement
The while statement allows you to repeatedly execute a block of statements as
long as a condition is true. A while statement is an example of what is called a
looping
statement. A while statement can have an optional else clause.
Example (save as while.py):
number =
23
running =
True
while
running:
guess =
int
(
input
(
'Enter an integer : '
))
if
guess == number:
(
'Congratulations, you guessed it.'
)
running =
False
# this causes the while loop to stop
elif
guess < number:
(
'No, it is a little higher than that.'
)
else
:
(
'No, it is a little lower than that.'
)
else
:
(
'The while loop is over.'
)
# Do anything else you want to do here
(
'Done'
)
Output:
43
$ python3 while.py
Enter an integer : 50
No, it is a little lower than that.
Enter an integer : 22
No, it is a little higher than that.
Enter an integer : 23
Congratulations, you guessed it.
The while loop is over.
Done
How It Works:
In this program, we are still playing the guessing game, but the advantage is
that the user is allowed to keep guessing until he guesses correctly - there is
no need to repeatedly run the program for each guess, as we have done in the
previous section. This aptly demonstrates the use of the while statement.
We move the input and if statements to inside the while loop and set the
variable running to True before the while loop. First, we check if the variable
running is True and then proceed to execute the corresponding while-block.
After this block is executed, the condition is again checked which in this case
is the running variable. If it is true, we execute the while-block again, else
we continue to execute the optional else-block and then continue to the next
statement.
The else block is executed when the while loop condition becomes False - this
may even be the first time that the condition is checked. If there is an else
clause for a while loop, it is always executed unless you break out of the loop
with a break statement.
The True and False are called Boolean types and you can consider them to be
equivalent to the value 1 and 0respectively.
Note for C/C++ Programmers
Remember that you can have an else
clause for the while loop.
8.3
The for loop
The for..in statement is another looping statement which iterates over a
sequence of objects i.e. go through each item in a sequence. We will see more
about
in detail in later chapters. What you need to know right now is
that a sequence is just an ordered collection of items.
Example (save as for.py):
for
i in
range
(
1
,
5
):
(i)
44
else
:
(
'The for loop is over'
)
Output:
$ python3 for.py
1
2
3
4
The for loop is over
How It Works:
In this program, we are printing a sequence of numbers. We generate this
sequence of numbers using the built-in range function.
What we do here is supply it two numbers and range returns a sequence of
numbers starting from the first number and up to the second number. For
example, range(1,5) gives the sequence [1, 2, 3, 4]. By default, range
takes a step count of 1. If we supply a third number to range, then that becomes
the step count. For example, range(1,5,2) gives [1,3]. Remember that the
range extends up to the second number i.e. it does not include the second
number.
Note that range() generates a sequence of numbers, but it will generate only one
number at a time, when the for loop requests for the next item. If you want
to see the full sequence of numbers immediately, use list(range()). Lists are
explained in the [
The for loop then iterates over this range - for i in range(1,5) is equivalent
to for i in [1, 2, 3, 4] which is like assigning each number (or object) in
the sequence to i, one at a time, and then executing the block of statements for
each value of i. In this case, we just print the value in the block of statements.
Remember that the else part is optional. When included, it is always executed
once after the for loop is over unless a [break][#break) statement is encountered.
Remember that the for..in loop works for any sequence. Here, we have a list
of numbers generated by the built-in range function, but in general we can use
any kind of sequence of any kind of objects! We will explore this idea in detail
in later chapters.
Note for C/C++/Java/C# Programmers
The Python for loop is radi-
cally different from the C/C++ for loop. C# programmers will note that
the for loop in Python is similar to the foreach loop in C#. Java pro-
grammers will note that the same is similar to for (int i : IntArray)
in Java 1.5 .
45
In C/C++, if you want to write for (int i = 0; i < 5; i++), then
in Python you write just for i in range(0,5). As you can see, the for
loop is simpler, more expressive and less error prone in Python.
8.4
The break Statement
The break statement is used to break out of a loop statement i.e. stop the
execution of a looping statement, even if the loop condition has not become
False or the sequence of items has not been completely iterated over.
An important note is that if you break out of a foror while loop, any corre-
sponding loop else block is not executed.
Example (save as break.py):
while
True
:
s =
input
(
'Enter something : '
)
if
s ==
'quit'
:
break
(
'Length of the string is'
,
len
(s))
(
'Done'
)
Output:
$ python3 break.py
Enter something : Programming is fun
Length of the string is 18
Enter something : When the work is done
Length of the string is 21
Enter something : if you wanna make your work also fun:
Length of the string is 37
Enter something :
use Python!
Length of the string is 12
Enter something : quit
Done
How It Works:
In this program, we repeatedly take the user’s input and print the length of each
input each time. We are providing a special condition to stop the program by
checking if the user input is ’quit’. We stop the program by breaking out of
the loop and reach the end of the program.
The length of the input string can be found out using the built-in len function.
Remember that the break statement can be used with the for loop as well.
46
8.4.1
Swaroop’s Poetic Python
The input I have used here is a mini poem I have written called Swaroop’s Poetic
Python
:
Programming is fun
When the work is done
if you wanna make your work also fun:
use Python!
8.5
The continue Statement
The continue statement is used to tell Python to skip the rest of the statements
in the current loop block and to continue to the next iteration of the loop.
Example (save as continue.py):
while
True
:
s =
input
(
'Enter something : '
)
if
s ==
'quit'
:
break
if
len
(s) <
3
:
(
'Too small'
)
continue
(
'Input is of sufficient length'
)
# Do other kinds of processing here...
Output:
$ python3 continue.py
Enter something : a
Too small
Enter something : 12
Too small
Enter something : abc
Input is of sufficient length
Enter something : quit
How It Works:
In this program, we accept input from the user, but we process the input string
only if it is at least 3 characters long. So, we use the built-in len function to get
the length and if the length is less than 3, we skip the rest of the statements in the
block by using the continue statement. Otherwise, the rest of the statements
in the loop are executed, doing any kind of processing we want to do here.
Note that the continue statement works with the forloop as well.
47
8.6
Summary
We have seen how to use the three control flow statements - if, while and for
along with their associated break and continue statements. These are some
of the most commonly used parts of Python and hence, becoming comfortable
with them is essential.
Next, we will see how to create and use functions.
9
Functions
Functions are reusable pieces of programs. They allow you to give a name to
a block of statements, allowing you to run that block using the specified name
anywhere in your program and any number of times. This is known as calling
the function. We have already used many built-in functions such as len and
range.
The function concept is probably the most important building block of any
non-trivial software (in any programming language), so we will explore various
aspects of functions in this chapter.
Functions are defined using the def keyword. After this keyword comes an
identifier
name for the function, followed by a pair of parentheses which may
enclose some names of variables, and by the final colon that ends the line. Next
follows the block of statements that are part of this function. An example will
show that this is actually very simple:
Example (save as function1.py):
def
sayHello():
(
'Hello World!'
)
# block belonging to the function
# End of function
sayHello()
# call the function
sayHello()
# call the function again
Output:
$ python3 function1.py
Hello World!
Hello World!
How It Works:
We define a function called sayHello using the syntax as explained above. This
function takes no parameters and hence there are no variables declared in the
48
parentheses. Parameters to functions are just input to the function so that we
can pass in different values to it and get back corresponding results.
Notice that we can call the same function twice which means we do not have to
write the same code again.
9.1
Function Parameters
A function can take parameters, which are values you supply to the function so
that the function can do something utilising those values. These parameters are
just like variables except that the values of these variables are defined when we
call the function and are already assigned values when the function runs.
Parameters are specified within the pair of parentheses in the function definition,
separated by commas. When we call the function, we supply the values in the
same way. Note the terminology used - the names given in the function definition
are called parameters whereas the values you supply in the function call are
called arguments.
Example (save as func_param.py):
def
printMax(a, b):
if
a > b:
(a,
'is maximum'
)
elif
a == b:
(a,
'is equal to'
, b)
else
:
(b,
'is maximum'
)
printMax(
3
,
4
)
# directly give literal values
x =
5
y =
7
printMax(x, y)
# give variables as arguments
Output:
$ python3 func_param.py
4 is maximum
7 is maximum
How It Works:
Here, we define a function called printMax that uses two parameters called a
and b. We find out the greater number using a simple if..else statement and
then print the bigger number.
49
The first time we call the function printMax, we directly supply the numbers as
arguments. In the second case, we call the function with variables as arguments.
printMax(x, y) causes the value of argument x to be assigned to parameter
a and the value of argument y to be assigned to parameter b. The printMax
function works the same way in both cases.
9.2
Local Variables
When you declare variables inside a function definition, they are not related
in any way to other variables with the same names used outside the function
- i.e. variable names are local to the function. This is called the scope of the
variable. All variables have the scope of the block they are declared in starting
from the point of definition of the name.
Example (save as func_local.py):
x =
50
def
func(x):
(
'x is'
, x)
x =
2
(
'Changed local x to'
, x)
func(x)
(
'x is still'
, x)
Output:
$ python3 func_local.py
x is 50
Changed local x to 2
x is still 50
How It Works:
The first time that we print the value of the name x with the first line in the
function’s body, Python uses the value of the parameter declared in the main
block, above the function definition.
Next, we assign the value 2 to x. The name x is local to our function. So, when
we change the value of x in the function, the x defined in the main block remains
unaffected.
With the last print function call, we display the value of x as defined in the main
block, thereby confirming that it is actually unaffected by the local assignment
within the previously called function.
50
9.3
Using The global Statement
If you want to assign a value to a name defined at the top level of the program
(i.e. not inside any kind of scope such as functions or classes), then you have to
tell Python that the name is not local, but it is global. We do this using the
global statement. It is impossible to assign a value to a variable defined outside
a function without the global statement.
You can use the values of such variables defined outside the function (assuming
there is no variable with the same name within the function). However, this is
not encouraged and should be avoided since it becomes unclear to the reader of
the program as to where that variable’s definition is. Using the global statement
makes it amply clear that the variable is defined in an outermost block.
Example (save as func_global.py):
x =
50
def
func():
global
x
(
'x is'
, x)
x =
2
(
'Changed global x to'
, x)
func()
(
'Value of x is'
, x)
Output:
$ python3 func_global.py
x is 50
Changed global x to 2
Value of x is 2
How It Works:
The global statement is used to declare that x is a global variable - hence, when
we assign a value to x inside the function, that change is reflected when we use
the value of x in the main block.
You can specify more than one global variable using the same global statement
e.g. global x, y, z.
51
9.4
Default Argument Values
For some functions, you may want to make some parameters optional and use
default values in case the user does not want to provide values for them. This is
done with the help of default argument values. You can specify default argument
values for parameters by appending to the parameter name in the function
definition the assignment operator (=) followed by the default value.
Note that the default argument value should be a constant. More precisely, the
default argument value should be immutable - this is explained in detail in later
chapters. For now, just remember this.
Example (save as func_default.py):
def
say(message, times =
1
):
(message * times)
say(
'Hello'
)
say(
'World'
,
5
)
Output:
$ python3 func_default.py
Hello
WorldWorldWorldWorldWorld
How It Works:
The function named say is used to print a string as many times as specified. If
we don’t supply a value, then by default, the string is printed just once. We
achieve this by specifying a default argument value of 1 to the parameter times.
In the first usage of say, we supply only the string and it prints the string once.
In the second usage of say, we supply both the string and an argument 5 stating
that we want to say the string message 5 times.
Important
Only those parameters which are at the end of the parameter list
can be given default argument values i.e. you cannot have a parameter
with a default argument value preceding a parameter without a default
argument value in the function’s parameter list.
This is because the values are assigned to the parameters by position. For
example,def func(a, b=5) is valid, but def func(a=5, b) is not valid.
52
9.5
Keyword Arguments
If you have some functions with many parameters and you want to specify only
some of them, then you can give values for such parameters by naming them
- this is called keyword arguments - we use the name (keyword) instead of the
position (which we have been using all along) to specify the arguments to the
function.
There are two advantages - one, using the function is easier since we do not need
to worry about the order of the arguments. Two, we can give values to only
those parameters to which we want to, provided that the other parameters have
default argument values.
Example (save as func_key.py):
def
func(a, b=
5
, c=
10
):
(
'a is'
, a,
'and b is'
, b,
'and c is'
, c)
func(
3
,
7
)
func(
25
, c=
24
)
func(c=
50
, a=
100
)
Output:
$ python3 func_key.py
a is 3 and b is 7 and c is 10
a is 25 and b is 5 and c is 24
a is 100 and b is 5 and c is 50
How It Works:
The function named func has one parameter without a default argument value,
followed by two parameters with default argument values.
In the first usage, func(3, 7), the parameter a gets the value 3, the parameter
b gets the value 7 and c gets the default value of 10.
In the second usage func(25, c=24), the variable a gets the value of 25 due to
the position of the argument. Then, the parameter c gets the value of 24 due to
naming i.e. keyword arguments. The variable b gets the default value of 5.
In the third usage func(c=50, a=100), we use keyword arguments for all speci-
fied values. Notice that we are specifying the value for parameter c before that
for a even though a is defined before c in the function definition.
53
9.6
VarArgs parameters
Sometimes you might want to define a function that can take any number of
parameters, this can be achieved by using the stars (save as total.py):
def
total(initial=
5
, *numbers, **keywords):
count = initial
for
number in numbers:
count += number
for
key in keywords:
count += keywords[key]
return
count
(total(
10
,
1
,
2
,
3
, vegetables=
50
, fruits=
100
))
Output:
$ python3 total.py
166
How It Works:
When we declare a starred parameter such as *param, then all the positional
arguments from that point till the end are collected as a tuple called ‘param’.
Similarly, when we declare a double-starred parameter such as **param, then all
the keyword arguments from that point till the end are collected as a dictionary
called ‘param’.
We will explore tuples and dictionaries in a
9.7
Keyword-only Parameters
If we want to specify certain keyword parameters to be available as keyword-only
and not as positional arguments, they can be declared after a starred parameter
(save as keyword_only.py):
def
total(initial=
5
, *numbers, extra_number):
count = initial
for
number in numbers:
count += number
count += extra_number
(count)
total(
10
,
1
,
2
,
3
, extra_number=
50
)
total(
10
,
1
,
2
,
3
)
# Raises error because we have not supplied a default argument value for 'extra_number'
54
Output:
$ python3 keyword_only.py
66
Traceback (most recent call last):
File "keyword_only.py", line 12, in <module>
total(10, 1, 2, 3)
TypeError: total() needs keyword-only argument extra_number
How It Works:
Declaring parameters after a starred parameter results in keyword-only arguments.
If these arguments are not supplied a default value, then calls to the function
will raise an error if the keyword argument is not supplied, as seen above.
Notice the use of += which is a shortcut operator, so instead of saying x = x +
y, you can say x += y.
If you want to have keyword-only arguments but have no need for a starred
parameter, then simply use an empty star without using any name such as def
total(initial=5, *, extra_number).
9.8
The return Statement
The return statement is used to return from a function i.e. break out of the
function. We can optionally return a value from the function as well.
Example (save as func_return.py):
def
maximum(x, y):
if
x > y:
return
x
elif
x == y:
return
'The numbers are equal'
else
:
return
y
(maximum(
2
,
3
))
Output:
$ python3 func_return.py
3
55
How It Works:
The maximum function returns the maximum of the parameters, in this case the
numbers supplied to the function. It uses a simple if..else statement to find
the greater value and then returns that value.
Note that a return statement without a value is equivalent to return None.
None is a special type in Python that represents nothingness. For example, it is
used to indicate that a variable has no value if it has a value of None.
Every function implicitly contains a return None statement at the end unless
you have written your own return statement. You can see this by running
print(someFunction()) where the function someFunction does not use the
return statement such as:
def
someFunction():
pass
The pass statement is used in Python to indicate an empty block of statements.
Note
There is a built-in function called max that already implements the ‘find
maximum’ functionality, so use this built-in function whenever possible.
9.9
DocStrings
Python has a nifty feature called documentation strings, usually referred to by
its shorter name docstrings. DocStrings are an important tool that you should
make use of since it helps to document the program better and makes it easier to
understand. Amazingly, we can even get the docstring back from, say a function,
when the program is actually running!
Example (save as func_doc.py):
def
printMax(x, y):
'''Prints the maximum of two numbers.
The two values must be integers.'''
x =
int
(x)
# convert to integers, if possible
y =
int
(y)
if
x > y:
(x,
'is maximum'
)
else
:
(y,
'is maximum'
)
printMax(
3
,
5
)
(printMax.__doc__)
56
Output:
$ python3 func_doc.py
5 is maximum
Prints the maximum of two numbers.
The two values must be integers.
How It Works:
A string on the first logical line of a function is the docstring for that function.
Note that DocStrings also apply to
and
which we will learn
about in the respective chapters.
The convention followed for a docstring is a multi-line string where the first
line starts with a capital letter and ends with a dot. Then the second line is
blank followed by any detailed explanation starting from the third line. You
are strongly advised to follow this convention for all your docstrings for all your
non-trivial functions.
We can access the docstring of the printMax function using the __doc__ (notice
the double underscores) attribute (name belonging to) of the function. Just
remember that Python treats everything as an object and this includes functions.
We’ll learn more about objects in the chapter on
If you have used help() in Python, then you have already seen the usage of
docstrings! What it does is just fetch the __doc__ attribute of that function
and displays it in a neat manner for you. You can try it out on the function
above - just include help(printMax) in your program. Remember to press the
q key to exit help.
Automated tools can retrieve the documentation from your program in this
manner. Therefore, I strongly recommend that you use docstrings for any non-
trivial function that you write. The pydoc command that comes with your
Python distribution works similarly to help() using docstrings.
9.10
Summary
We have seen so many aspects of functions but note that we still haven’t covered
all aspects of them. However, we have already covered most of what you’ll use
regarding Python functions on an everyday basis.
Next, we will see how to use as well as create Python modules.
57
10
Modules
You have seen how you can reuse code in your program by defining functions
once. What if you wanted to reuse a number of functions in other programs that
you write? As you might have guessed, the answer is modules.
There are various methods of writing modules, but the simplest way is to create
a file with a .py extension that contains functions and variables.
Another method is to write the modules in the native language in which the
Python interpreter itself was written. For example, you can write modules in
the
and when compiled, they can be used from your
Python code when using the standard Python interpreter.
A module can be imported by another program to make use of its functionality.
This is how we can use the Python standard library as well. First, we will see
how to use the standard library modules.
Example (save as using_sys.py):
import
sys
(
'The command line arguments are:'
)
for
i in sys.argv:
(i)
(
'\n\nThe PYTHONPATH is'
, sys.path,
'\n'
)
Output:
$ python3 using_sys.py we are arguments
The command line arguments are:
using_sys.py
we
are
arguments
The PYTHONPATH is [<nowiki>''</nowiki>, 'C:\\Windows\\system32\\python30.zip',
'C:\\Python30\\DLLs', 'C:\\Python30\\lib',
'C:\\Python30\\lib\\plat-win', 'C:\\Python30',
'C:\\Python30\\lib\\site-packages']
How It Works:
First, we import the sys module using the import statement. Basically, this
translates to us telling Python that we want to use this module. The sys module
58
contains functionality related to the Python interpreter and its environment
i.e. the system.
When Python executes the import sys statement, it looks for the sys module.
In this case, it is one of the built-in modules, and hence Python knows where to
find it.
If it was not a compiled module i.e. a module written in Python, then the Python
interpreter will search for it in the directories listed in its sys.path variable. If
the module is found, then the statements in the body of that module are run
and the module is made available for you to use. Note that the initialization is
done only the first time that we import a module.
The argv variable in the sys module is accessed using the dotted notation
i.e. sys.argv. It clearly indicates that this name is part of the sys module.
Another advantage of this approach is that the name does not clash with any
argv variable used in your program.
The sys.argv variable is a list of strings (lists are explained in detail in a
). Specifically, the sys.argv contains the list of command line arguments
i.e. the arguments passed to your program using the command line.
If you are using an IDE to write and run these programs, look for a way to
specify command line arguments to the program in the menus.
Here, when we execute python using_sys.py we are arguments, we run the
module using_sys.py with the python command and the other things that
follow are arguments passed to the program. Python stores the command line
arguments in the sys.argv variable for us to use.
Remember, the name of the script running is always the first argument in the
sys.argv list. So, in this case we will have ’using_sys.py’ as sys.argv[0],
’we’ as sys.argv[1], ’are’ as sys.argv[2] and ’arguments’ as sys.argv[3].
Notice that Python starts counting from 0 and not 1.
The sys.path contains the list of directory names where modules are imported
from. Observe that the first string in sys.path is empty - this empty string
indicates that the current directory is also part of the sys.path which is same as
the PYTHONPATH environment variable. This means that you can directly import
modules located in the current directory. Otherwise, you will have to place your
module in one of the directories listed in sys.path.
Note that the current directory is the directory from which the program is
launched. Run import os; print(os.getcwd()) to find out the current direc-
tory of your program.
10.1
Byte-compiled .pyc files
Importing a module is a relatively costly affair, so Python does some tricks
to make it faster. One way is to create byte-compiled files with the extension
59
.pyc which is an intermediate form that Python transforms the program into
(remember the
on how Python works?). This .pyc file is
useful when you import the module the next time from a different program -
it will be much faster since a portion of the processing required in importing a
module is already done. Also, these byte-compiled files are platform-independent.
Note
These .pyc files are usually created in the same directory as the corre-
sponding .py files. If Python does not have permission to write to files in
that directory, then the .pyc files will not be created.
10.2
The from . . . import statement
If you want to directly import the argv variable into your program (to avoid
typing the sys. everytime for it), then you can use the from sys import argv
statement.
In general, you should avoid using this statement and use the import statement
instead since your program will avoid name clashes and will be more readable.
Example:
from
math
import
sqrt
(
"Square root of 16 is"
, sqrt(
16
))
10.3
A module’s name
Every module has a name and statements in a module can find out the name of
their module. This is handy for the particular purpose of figuring out whether
the module is being run standalone or being imported. As mentioned previously,
when a module is imported for the first time, the code it contains gets executed.
We can use this to make the module behave in different ways depending on
whether it is being used by itself or being imported from another module. This
can be achieved using the __name__ attribute of the module.
Example (save as using_name.py):
if
__name__
==
'__main__'
:
(
'This program is being run by itself'
)
else
:
(
'I am being imported from another module'
)
Output:
60
$ python3 using_name.py
This program is being run by itself
$ python3
>>> import using_name
I am being imported from another module
>>>
How It Works:
Every Python module has its __name__ defined. If this is ’__main__’, that
implies that the module is being run standalone by the user and we can take
appropriate actions.
10.4
Making Your Own Modules
Creating your own modules is easy, you’ve been doing it all along! This is
because every Python program is also a module. You just have to make sure it
has a .py extension. The following example should make it clear.
Example (save as mymodule.py):
def
sayhi():
(
'Hi, this is mymodule speaking.'
)
__version__ =
'0.1'
The above was a sample module. As you can see, there is nothing particularly
special about it compared to our usual Python program. We will next see how
to use this module in our other Python programs.
Remember that the module should be placed either in the same directory as the
program from which we import it, or in one of the directories listed in sys.path.
Another module (save as mymodule_demo.py):
import
mymodule
mymodule.sayhi()
(
'Version'
, mymodule.__version__)
Output:
$ python3 mymodule_demo.py
Hi, this is mymodule speaking.
Version 0.1
61
How It Works:
Notice that we use the same dotted notation to access members of the module.
Python makes good reuse of the same notation to give the distinctive ‘Pythonic’
feel to it so that we don’t have to keep learning new ways to do things.
Here is a version utilising the from..import syntax (save as mymodule_demo2.py):
from
mymodule
import
sayhi, __version__
sayhi()
(
'Version'
, __version__)
The output of mymodule_demo2.py is same as the output of mymodule_demo.py.
Notice that if there was already a __version__ name declared in the module
that imports mymodule, there would be a clash. This is also likely because it
is common practice for each module to declare it’s version number using this
name. Hence, it is always recommended to prefer the import statement even
though it might make your program a little longer.
You could also use:
from
mymodule
import
*
This will import all public names such as sayhi but would not import
__version__ because it starts with double underscores.
Zen of Python
One of Python’s guiding principles is that “Explicit is better
than Implicit”. Run import this to learn more and see
which lists examples for each of the principles.
10.5
The dir function
You can use the built-in dir function to list the identifiers that an object defines.
For example, for a module, the identifiers include the functions, classes and
variables defined in that module.
When you supply a module name to thedir() function, it returns the list of the
names defined in that module. When no argument is applied to it, it returns
the list of names defined in the current module.
Example:
$ python3
62
>>> import sys # get list of attributes, in this case, for the sys module
>>> dir(sys)
['__displayhook__', '__doc__', '__excepthook__', '__name__', '__package__', '__s
tderr__', '__stdin__', '__stdout__', '_clear_type_cache', '_compact_freelists',
'_current_frames', '_getframe', 'api_version', 'argv', 'builtin_module_names', '
byteorder', 'call_tracing', 'callstats', 'copyright', 'displayhook', 'dllhandle'
, 'dont_write_bytecode', 'exc_info', 'excepthook', 'exec_prefix', 'executable',
'exit', 'flags', 'float_info', 'getcheckinterval', 'getdefaultencoding', 'getfil
esystemencoding', 'getprofile', 'getrecursionlimit', 'getrefcount', 'getsizeof',
'gettrace', 'getwindowsversion', 'hexversion', 'intern', 'maxsize', 'maxunicode
', 'meta_path', 'modules', 'path', 'path_hooks', 'path_importer_cache', 'platfor
m', 'prefix', 'ps1', 'ps2', 'setcheckinterval', 'setprofile', 'setrecursionlimit
', 'settrace', 'stderr', 'stdin', 'stdout', 'subversion', 'version', 'version_in
fo', 'warnoptions', 'winver']
>>> dir() # get list of attributes for current module
['__builtins__', '__doc__', '__name__', '__package__', 'sys']
>>> a = 5 # create a new variable 'a'
>>> dir()
['__builtins__', '__doc__', '__name__', '__package__', 'a', 'sys']
>>> del a # delete/remove a name
>>> dir()
['__builtins__', '__doc__', '__name__', '__package__', 'sys']
>>>
How It Works:
First, we see the usage of dir on the imported sys module. We can see the
huge list of attributes that it contains.
Next, we use the dir function without passing parameters to it. By default,
it returns the list of attributes for the current module. Notice that the list of
imported modules is also part of this list.
In order to observe the dir in action, we define a new variable a and assign it a
value and then check dirand we observe that there is an additional value in the
list of the same name. We remove the variable/attribute of the current module
using the del statement and the change is reflected again in the output of the
dir function.
A note on del - this statement is used to delete a variable/name and after the
statement has run, in this case del a, you can no longer access the variable a -
63
it is as if it never existed before at all.
Note that the dir() function works on any object.
For example, run
dir(’print’) to learn about the attributes of the print function, or dir(str)
for the attributes of the str class.
10.6
Packages
By now, you must have started observing the hierarchy of organizing your
programs. Variables usually go inside functions. Functions and global variables
usually go inside modules. What if you wanted to organize modules? That’s
where packages come into the picture.
Packages are just folders of modules with a special __init__.py file that indicates
to Python that this folder is special because it contains Python modules.
Let’s say you want to create a package called ‘world’ with subpackages ‘asia’,
‘africa’, etc. and these subpackages in turn contain modules like ‘india’, ‘mada-
gascar’, etc.
This is how you would structure the folders:
- <some folder present in the sys.path>/
- world/
- __init__.py
- asia/
- __init__.py
- india/
- __init__.py
- foo.py
- africa/
- __init__.py
- madagascar/
- __init__.py
- bar.py
Packages are just a convenience to hierarchically organize modules. You will see
many instances of this in the
10.7
Summary
Just like functions are reusable parts of programs, modules are reusable programs.
Packages are another hierarchy to organize modules. The standard library that
comes with Python is an example of such a set of packages and modules.
We have seen how to use these modules and create our own modules.
Next, we will learn about some interesting concepts called data structures.
64
11
Data Structures
Data structures are basically just that - they are structures which can hold some
data
together. In other words, they are used to store a collection of related data.
There are four built-in data structures in Python - list, tuple, dictionary and set.
We will see how to use each of them and how they make life easier for us.
11.1
List
A list is a data structure that holds an ordered collection of items i.e. you can
store a sequence of items in a list. This is easy to imagine if you can think of a
shopping list where you have a list of items to buy, except that you probably
have each item on a separate line in your shopping list whereas in Python you
put commas in between them.
The list of items should be enclosed in square brackets so that Python understands
that you are specifying a list. Once you have created a list, you can add, remove
or search for items in the list. Since we can add and remove items, we say that
a list is a mutable data type i.e. this type can be altered.
11.1.1
Quick Introduction To Objects And Classes
Although I’ve been generally delaying the discussion of objects and classes till
now, a little explanation is needed right now so that you can understand lists
better. We will explore this topic in detail in a
A list is an example of usage of objects and classes. When we use a variable i
and assign a value to it, say integer 5 to it, you can think of it as creating an
object
(i.e. instance) i of class (i.e. type) int. In fact, you can read help(int)
to understand this better.
A class can also have methods i.e. functions defined for use with respect to
that class only. You can use these pieces of functionality only when you have an
object of that class. For example, Python provides an append method for the
list class which allows you to add an item to the end of the list. For example,
mylist.append(’an item’) will add that string to the list mylist. Note the
use of dotted notation for accessing methods of the objects.
A class can also have fields which are nothing but variables defined for use with
respect to that class only. You can use these variables/names only when you
have an object of that class. Fields are also accessed by the dotted notation, for
example, mylist.field.
Example (save as using_list.py):
65
# This is my shopping list
shoplist = [
'apple'
,
'mango'
,
'carrot'
,
'banana'
]
(
'I have'
,
len
(shoplist),
'items to purchase.'
)
(
'These items are:'
, end=
' '
)
for
item in shoplist:
(item, end=
' '
)
(
'\nI also have to buy rice.'
)
shoplist.append(
'rice'
)
(
'My shopping list is now'
, shoplist)
(
'I will sort my list now'
)
shoplist.sort()
(
'Sorted shopping list is'
, shoplist)
(
'The first item I will buy is'
, shoplist[
0
])
olditem = shoplist[
0
]
del
shoplist[
0
]
(
'I bought the'
, olditem)
(
'My shopping list is now'
, shoplist)
Output:
$ python3 using_list.py
I have 4 items to purchase.
These items are: apple mango carrot banana
I also have to buy rice.
My shopping list is now ['apple', 'mango', 'carrot', 'banana', 'rice']
I will sort my list now
Sorted shopping list is ['apple', 'banana', 'carrot', 'mango', 'rice']
The first item I will buy is apple
I bought the apple
My shopping list is now ['banana', 'carrot', 'mango', 'rice']
How It Works:
The variable shoplist is a shopping list for someone who is going to the market.
In shoplist, we only store strings of the names of the items to buy but you can
add any kind of object to a list including numbers and even other lists.
We have also used the for..in loop to iterate through the items of the list. By
now, you must have realised that a list is also a sequence. The speciality of
sequences will be discussed in a
66
Notice the use of the end keyword argument to the print function to indicate
that we want to end the output with a space instead of the usual line break.
Next, we add an item to the list using the append method of the list object, as
already discussed before. Then, we check that the item has been indeed added
to the list by printing the contents of the list by simply passing the list to the
print statement which prints it neatly.
Then, we sort the list by using the sort method of the list. It is important to
understand that this method affects the list itself and does not return a modified
list - this is different from the way strings work. This is what we mean by saying
that lists are mutable and that strings are immutable.
Next, when we finish buying an item in the market, we want to remove it from
the list. We achieve this by using the del statement. Here, we mention which
item of the list we want to remove and the del statement removes it from the
list for us. We specify that we want to remove the first item from the list and
hence we use del shoplist[0] (remember that Python starts counting from 0).
If you want to know all the methods defined by the list object, see help(list)
for details.
11.2
Tuple
Tuples are used to hold together multiple objects. Think of them as similar to
lists, but without the extensive functionality that the list class gives you. One
major feature of tuples is that they are immutable like strings i.e. you cannot
modify tuples.
Tuples are defined by specifying items separated by commas within an optional
pair of parentheses.
Tuples are usually used in cases where a statement or a user-defined function
can safely assume that the collection of values i.e. the tuple of values used will
not change.
Example (save as using_tuple.py):
zoo = (
'python'
,
'elephant'
,
'penguin'
)
# remember the parentheses are optional
(
'Number of animals in the zoo is'
,
len
(zoo))
new_zoo =
'monkey'
,
'camel'
, zoo
(
'Number of cages in the new zoo is'
,
len
(new_zoo))
(
'All animals in new zoo are'
, new_zoo)
(
'Animals brought from old zoo are'
, new_zoo[
2
])
(
'Last animal brought from old zoo is'
, new_zoo[
2
][
2
])
(
'Number of animals in the new zoo is'
,
len
(new_zoo)-
1
+
len
(new_zoo[
2
]))
67
Output:
$ python3 using_tuple.py
Number of animals in the zoo is 3
Number of cages in the new zoo is 3
All animals in new zoo are ('monkey', 'camel', ('python', 'elephant', 'penguin'))
Animals brought from old zoo are ('python', 'elephant', 'penguin')
Last animal brought from old zoo is penguin
Number of animals in the new zoo is 5
How It Works:
The variable zoo refers to a tuple of items. We see that the len function can be
used to get the length of the tuple. This also indicates that a tuple is a
as well.
We are now shifting these animals to a new zoo since the old zoo is being closed.
Therefore, the new_zoo tuple contains some animals which are already there
along with the animals brought over from the old zoo. Back to reality, note that
a tuple within a tuple does not lose its identity.
We can access the items in the tuple by specifying the item’s position within
a pair of square brackets just like we did for lists. This is called the indexing
operator. We access the third item in new_zoo by specifying new_zoo[2] and
we access the third item within the third item in the new_zoo tuple by specifying
new_zoo[2][2]. This is pretty simple once you’ve understood the idiom.
Parentheses
Although the parentheses are optional, I prefer always having
them to make it obvious that it is a tuple, especially because it avoids
ambiguity. For example, print(1,2,3) and print( (1,2,3) ) mean two
different things - the former prints three numbers whereas the latter prints
a tuple (which contains three numbers).
Tuple with 0 or 1 items
An empty tuple is constructed by an empty pair of
parentheses such as myempty = (). However, a tuple with a single item
is not so simple. You have to specify it using a comma following the first
(and only) item so that Python can differentiate between a tuple and a
pair of parentheses surrounding the object in an expression i.e. you have
to specify singleton = (2 , ) if you mean you want a tuple containing
the item 2.
Note for Perl programmers
A list within a list does not lose its identity
i.e. lists are not flattened as in Perl. The same applies to a tuple within
a tuple, or a tuple within a list, or a list within a tuple, etc. As far as
Python is concerned, they are just objects stored using another object,
that’s all.
68
11.3
Dictionary
A dictionary is like an address-book where you can find the address or contact
details of a person by knowing only his/her name i.e. we associate keys (name)
with values (details). Note that the key must be unique just like you cannot
find out the correct information if you have two persons with the exact same
name.
Note that you can use only immutable objects (like strings) for the keys of a
dictionary but you can use either immutable or mutable objects for the values of
the dictionary. This basically translates to say that you should use only simple
objects for keys.
Pairs of keys and values are specified in a dictionary by using the notation d
= {key1 : value1, key2 : value2 }. Notice that the key-value pairs are
separated by a colon and the pairs are separated themselves by commas and all
this is enclosed in a pair of curly braces.
Remember that key-value pairs in a dictionary are not ordered in any manner.
If you want a particular order, then you will have to sort them yourself before
using it.
The dictionaries that you will be using are instances/objects of the dict class.
Example (save as using_dict.py):
# 'ab' is short for 'a'ddress'b'ook
ab = {
'Swaroop'
:
'swaroop@swaroopch.com'
,
'Larry'
:
'larry@wall.org'
,
'Matsumoto'
:
'matz@ruby-lang.org'
,
'Spammer'
:
'spammer@hotmail.com'
}
(
"Swaroop's address is"
, ab[
'Swaroop'
])
# Deleting a key-value pair
del
ab[
'Spammer'
]
(
'\nThere are {0} contacts in the address-book\n'
.
format
(
len
(ab)))
for
name, address in ab.items():
(
'Contact {0} at {1}'
.
format
(name, address))
# Adding a key-value pair
ab[
'Guido'
] =
'guido@python.org'
if
'Guido'
in ab:
(
"\nGuido's address is"
, ab[
'Guido'
])
69
Output:
$ python3 using_dict.py
Swaroop's address is swaroop@swaroopch.com
There are 3 contacts in the address-book
Contact Swaroop at swaroop@swaroopch.com
Contact Matsumoto at matz@ruby-lang.org
Contact Larry at larry@wall.org
Guido's address is guido@python.org
How It Works:
We create the dictionary ab using the notation already discussed. We then access
key-value pairs by specifying the key using the indexing operator as discussed in
the context of lists and tuples. Observe the simple syntax.
We can delete key-value pairs using our old friend - the del statement. We simply
specify the dictionary and the indexing operator for the key to be removed and
pass it to the del statement. There is no need to know the value corresponding
to the key for this operation.
Next, we access each key-value pair of the dictionary using the items method of
the dictionary which returns a list of tuples where each tuple contains a pair of
items - the key followed by the value. We retrieve this pair and assign it to the
variables name and address correspondingly for each pair using the for..in
loop and then print these values in the for-block.
We can add new key-value pairs by simply using the indexing operator to access
a key and assign that value, as we have done for Guido in the above case.
We can check if a key-value pair exists using the in operator.
For the list of methods of the dict class, see help(dict).
Keyword Arguments and Dictionaries
On a different note, if you have
used keyword arguments in your functions, you have already used dictio-
naries! Just think about it - the key-value pair is specified by you in the
parameter list of the function definition and when you access variables
within your function, it is just a key access of a dictionary (which is called
the symbol table in compiler design terminology).
11.4
Sequence
Lists, tuples and strings are examples of sequences, but what are sequences and
what is so special about them?
70
The major features are membership tests, (i.e. the in and not in expressions)
and indexing operations, which allow us to fetch a particular item in the
sequence directly.
The three types of sequences mentioned above - lists, tuples and strings, also
have a slicing operation which allows us to retrieve a slice of the sequence i.e. a
part of the sequence.
Example (save as seq.py):
shoplist = [
'apple'
,
'mango'
,
'carrot'
,
'banana'
]
name =
'swaroop'
# Indexing or 'Subscription' operation
(
'Item 0 is'
, shoplist[
0
])
(
'Item 1 is'
, shoplist[
1
])
(
'Item 2 is'
, shoplist[
2
])
(
'Item 3 is'
, shoplist[
3
])
(
'Item -1 is'
, shoplist[-
1
])
(
'Item -2 is'
, shoplist[-
2
])
(
'Character 0 is'
, name[
0
])
# Slicing on a list
(
'Item 1 to 3 is'
, shoplist[
1
:
3
])
(
'Item 2 to end is'
, shoplist[
2
:])
(
'Item 1 to -1 is'
, shoplist[
1
:-
1
])
(
'Item start to end is'
, shoplist[:])
# Slicing on a string
(
'characters 1 to 3 is'
, name[
1
:
3
])
(
'characters 2 to end is'
, name[
2
:])
(
'characters 1 to -1 is'
, name[
1
:-
1
])
(
'characters start to end is'
, name[:])
Output:
$ python3 seq.py
Item 0 is apple
Item 1 is mango
Item 2 is carrot
Item 3 is banana
Item -1 is banana
Item -2 is carrot
Character 0 is s
Item 1 to 3 is ['mango', 'carrot']
Item 2 to end is ['carrot', 'banana']
71
Item 1 to -1 is ['mango', 'carrot']
Item start to end is ['apple', 'mango', 'carrot', 'banana']
characters 1 to 3 is wa
characters 2 to end is aroop
characters 1 to -1 is waroo
characters start to end is swaroop
How It Works:
First, we see how to use indexes to get individual items of a sequence. This is
also referred to as the subscription operation. Whenever you specify a number
to a sequence within square brackets as shown above, Python will fetch you the
item corresponding to that position in the sequence. Remember that Python
starts counting numbers from 0. Hence, shoplist[0] fetches the first item and
shoplist[3] fetches the fourth item in the shoplistsequence.
The index can also be a negative number, in which case, the position is calculated
from the end of the sequence. Therefore, shoplist[-1] refers to the last item
in the sequence and shoplist[-2] fetches the second last item in the sequence.
The slicing operation is used by specifying the name of the sequence followed by
an optional pair of numbers separated by a colon within square brackets. Note
that this is very similar to the indexing operation you have been using till now.
Remember the numbers are optional but the colon isn’t.
The first number (before the colon) in the slicing operation refers to the position
from where the slice starts and the second number (after the colon) indicates
where the slice will stop at. If the first number is not specified, Python will
start at the beginning of the sequence. If the second number is left out, Python
will stop at the end of the sequence. Note that the slice returned starts at the
start position and will end just before the end position i.e. the start position is
included but the end position is excluded from the sequence slice.
Thus, shoplist[1:3] returns a slice of the sequence starting at position 1,
includes position 2 but stops at position 3 and therefore a slice of two items is
returned. Similarly, shoplist[:] returns a copy of the whole sequence.
You can also do slicing with negative positions. Negative numbers are used for
positions from the end of the sequence. For example, shoplist[:-1] will return
a slice of the sequence which excludes the last item of the sequence but contains
everything else.
You can also provide a third argument for the slice, which is the step for the
slicing (by default, the step size is 1):
>>> shoplist = ['apple', 'mango', 'carrot', 'banana']
>>> shoplist[::1]
['apple', 'mango', 'carrot', 'banana']
>>> shoplist[::2]
72
['apple', 'carrot']
>>> shoplist[::3]
['apple', 'banana']
>>> shoplist[::-1]
['banana', 'carrot', 'mango', 'apple']
Notice that when the step is 2, we get the items with position 0, 2, . . . When
the step size is 3, we get the items with position 0, 3, etc.
Try various combinations of such slice specifications using the Python interpreter
interactively i.e. the prompt so that you can see the results immediately. The
great thing about sequences is that you can access tuples, lists and strings all in
the same way!
11.5
Set
Sets are unordered collections of simple objects. These are used when the
existence of an object in a collection is more important than the order or how
many times it occurs.
Using sets, you can test for membership, whether it is a subset of another set,
find the intersection between two sets, and so on.
>>> bri = set(['brazil', 'russia', 'india'])
>>> 'india' in bri
True
>>> 'usa' in bri
False
>>> bric = bri.copy()
>>> bric.add('china')
>>> bric.issuperset(bri)
True
>>> bri.remove('russia')
>>> bri & bric # OR bri.intersection(bric)
{'brazil', 'india'}
How It Works:
The example is pretty much self-explanatory because it involves basic set theory
mathematics taught in school.
11.6
References
When you create an object and assign it to a variable, the variable only refers to
the object and does not represent the object itself! That is, the variable name
73
points to that part of your computer’s memory where the object is stored. This
is called binding the name to the object.
Generally, you don’t need to be worried about this, but there is a subtle effect
due to references which you need to be aware of:
Example (save as reference.py):
(
'Simple Assignment'
)
shoplist = [
'apple'
,
'mango'
,
'carrot'
,
'banana'
]
mylist = shoplist
# mylist is just another name pointing to the same object!
del
shoplist[
0
]
# I purchased the first item, so I remove it from the list
(
'shoplist is'
, shoplist)
(
'mylist is'
, mylist)
# notice that both shoplist and mylist both print the same list without
# the 'apple' confirming that they point to the same object
(
'Copy by making a full slice'
)
mylist = shoplist[:]
# make a copy by doing a full slice
del
mylist[
0
]
# remove first item
(
'shoplist is'
, shoplist)
(
'mylist is'
, mylist)
# notice that now the two lists are different
Output:
$ python3 reference.py
Simple Assignment
shoplist is ['mango', 'carrot', 'banana']
mylist is ['mango', 'carrot', 'banana']
Copy by making a full slice
shoplist is ['mango', 'carrot', 'banana']
mylist is ['carrot', 'banana']
How It Works:
Most of the explanation is available in the comments.
Remember that if you want to make a copy of a list or such kinds of sequences
or complex objects (not simple objects such as integers), then you have to use
the slicing operation to make a copy. If you just assign the variable name to
another name, both of them will ‘’refer” to the same object and this could be
trouble if you are not careful.
74
Note for Perl programmers
Remember that an assignment statement for
lists does not create a copy. You have to use slicing operation to make a
copy of the sequence.
11.7
More About Strings
We have already discussed strings in detail earlier. What more can there be to
know? Well, did you know that strings are also objects and have methods which
do everything from checking part of a string to stripping spaces!
The strings that you use in program are all objects of the class str. Some useful
methods of this class are demonstrated in the next example. For a complete list
of such methods, see help(str).
Example (save as str_methods.py):
name =
'Swaroop'
# This is a string object
if
name.startswith(
'Swa'
):
(
'Yes, the string starts with "Swa"'
)
if
'a'
in name:
(
'Yes, it contains the string "a"'
)
if
name.find(
'war'
) != -
1
:
(
'Yes, it contains the string "war"'
)
delimiter =
'_*_'
mylist = [
'Brazil'
,
'Russia'
,
'India'
,
'China'
]
(delimiter.join(mylist))
Output:
$ python3 str_methods.py
Yes, the string starts with "Swa"
Yes, it contains the string "a"
Yes, it contains the string "war"
Brazil_*_Russia_*_India_*_China
How It Works:
Here, we see a lot of the string methods in action. The startswith method is
used to find out whether the string starts with the given string. The in operator
is used to check if a given string is a part of the string.
75
The find method is used to locate the position of the given substring within
the string; find returns -1 if it is unsuccessful in finding the substring. The str
class also has a neat method to join the items of a sequence with the string
acting as a delimiter between each item of the sequence and returns a bigger
string generated from this.
11.8
Summary
We have explored the various built-in data structures of Python in detail. These
data structures will be essential for writing programs of reasonable size.
Now that we have a lot of the basics of Python in place, we will next see how to
design and write a real-world Python program.
12
Problem Solving
We have explored various parts of the Python language and now we will take
a look at how all these parts fit together, by designing and writing a program
which does something useful. The idea is to learn how to write a Python script
on your own.
12.1
The Problem
The problem we want to solve is “I want a program which creates a backup of
all my important files”
.
Although, this is a simple problem, there is not enough information for us to get
started with the solution. A little more analysis is required. For example, how
do we specify which files are to be backed up? How are they stored? Where are
they stored?
After analyzing the problem properly, we design our program. We make a list
of things about how our program should work. In this case, I have created the
following list on how I want it to work. If you do the design, you may not come
up with the same kind of analysis since every person has their own way of doing
things, so that is perfectly okay.
• The files and directories to be backed up are specified in a list.
• The backup must be stored in a main backup directory.
• The files are backed up into a zip file.
• The name of the zip archive is the current date and time.
• We use the standard zip command available by default in any standard
Linux/Unix distribution. Windows users can
from the
and add C:\Program Files\GnuWin32\bin to your system
PATH environment variable, similar to
what we did for recognizing the
. Note that you can use any archiving command
you want as long as it has a command line
12.2
The Solution
As the design of our program is now reasonably stable, we can write the code
which is an implementation of our solution.
Save as backup_ver1.py:
import
os
import
time
# 1. The files and directories to be backed up are specified in a list.
source = [
'"C:\\My Documents"'
,
'C:\\Code'
]
# Notice we had to use double quotes inside the string for names with spaces in it.
# 2. The backup must be stored in a main backup directory
target_dir =
'E:\\Backup'
# Remember to change this to what you will be using
# 3. The files are backed up into a zip file.
# 4. The name of the zip archive is the current date and time
target = target_dir + os.sep + time.strftime(
'%Y%m
%d
%H%M%S'
) +
'.zip'
# 5. We use the zip command to put the files in a zip archive
zip_command =
"zip -qr {0} {1}"
.
format
(target,
' '
.join(source))
# Run the backup
if
os.system(zip_command) ==
0
:
(
'Successful backup to'
, target)
else
:
(
'Backup FAILED'
)
Output:
$ python backup_ver1.py
Successful backup to E:\Backup\20080702185040.zip
Now, we are in the testing phase where we test that our program works properly.
If it doesn’t behave as expected, then we have to debug our program i.e. remove
the bugs (errors) from the program.
If the above program does not work for you, put a print(zip_command) just
before the os.system call and run the program. Now copy/paste the printed
77
zip_command to the shell prompt and see if it runs properly on its own. If this
command fails, check the zip command manual on what could be wrong. If this
command succeeds, then check the Python program if it exactly matches the
program written above.
How It Works:
You will notice how we have converted our design into code in a step-by-step
manner.
We make use of the os and time modules by first importing them. Then, we
specify the files and directories to be backed up in the source list. The target
directory is where we store all the backup files and this is specified in the
target_dir variable. The name of the zip archive that we are going to create is
the current date and time which we generate using the time.strftime() function.
It will also have the .zip extension and will be stored in the target_dir
directory.
Notice the use of the os.sep variable - this gives the directory separator according
to your operating system i.e. it will be ’/’ in Linux and Unix, it will be ’\\’ in
Windows and ’:’ in Mac OS. Using os.sep instead of these characters directly
will make our program portable and work across all of these systems.
The time.strftime() function takes a specification such as the one we have
used in the above program. The %Y specification will be replaced by the year
with the century. The %m specification will be replaced by the month as a decimal
number between 01 and 12 and so on. The complete list of such specifications
can be found in the
We create the name of the target zip file using the addition operator which
concatenates
the strings i.e. it joins the two strings together and returns a new
one. Then, we create a string zip_command which contains the command that
we are going to execute. You can check if this command works by running it in
the shell (Linux terminal or DOS prompt).
The zip command that we are using has some options and parameters passed.
The -q option is used to indicate that the zip command should work quietly. The
-r option specifies that the zip command should work recursively for directories
i.e. it should include all the subdirectories and files. The two options are combined
and specified in a shortcut as -qr. The options are followed by the name of the
zip archive to create followed by the list of files and directories to backup. We
convert the source list into a string using the join method of strings which we
have already seen how to use.
Then, we finally run the command using the os.system function which runs the
command as if it was run from the system i.e. in the shell - it returns 0 if the
command was successfully, else it returns an error number.
Depending on the outcome of the command, we print the appropriate message
that the backup has failed or succeeded.
78
That’s it, we have created a script to take a backup of our important files!
Note to Windows Users
Instead of double backslash escape sequences,
you can also use raw strings. For example, use ’C:\\Documents’ or
r’C:\Documents’. However, do not use ’C:\Documents’ since you end
up using an unknown escape sequence \D.
Now that we have a working backup script, we can use it whenever we want to
take a backup of the files. Linux/Unix users are advised to use the
as discussed earlier so that they can run the backup script anytime
anywhere. This is called the operation phase or the deployment phase of the
software.
The above program works properly, but (usually) first programs do not work
exactly as you expect. For example, there might be problems if you have not
designed the program properly or if you have made a mistake when typing the
code, etc. Appropriately, you will have to go back to the design phase or you
will have to debug your program.
12.3
Second Version
The first version of our script works. However, we can make some refinements to
it so that it can work better on a daily basis. This is called the maintenance
phase of the software.
One of the refinements I felt was useful is a better file-naming mechanism - using
the time as the name of the file within a directory with the current date as a
directory within the main backup directory. The first advantage is that your
backups are stored in a hierarchical manner and therefore it is much easier to
manage. The second advantage is that the filenames are much shorter. The
third advantage is that separate directories will help you check if you have made
a backup for each day since the directory would be created only if you have
made a backup for that day.
Save as backup_ver2.py:
import
os
import
time
# 1. The files and directories to be backed up are specified in a list.
source = [
'"C:\\My Documents"'
,
'C:\\Code'
]
# Notice we had to use double quotes inside the string for names with spaces in it.
# 2. The backup must be stored in a main backup directory
target_dir =
'E:\\Backup'
# Remember to change this to what you will be using
79
# 3. The files are backed up into a zip file.
# 4. The current day is the name of the subdirectory in the main directory
today = target_dir + os.sep + time.strftime(
'%Y%m
%d
'
)
# The current time is the name of the zip archive
now = time.strftime(
'%H%M%S'
)
# Create the subdirectory if it isn't already there
if
not os.path.exists(today):
os.mkdir(today)
# make directory
(
'Successfully created directory'
, today)
# The name of the zip file
target = today + os.sep + now +
'.zip'
# 5. We use the zip command to put the files in a zip archive
zip_command =
"zip -qr {0} {1}"
.
format
(target,
' '
.join(source))
# Run the backup
if
os.system(zip_command) ==
0
:
(
'Successful backup to'
, target)
else
:
(
'Backup FAILED'
)
Output:
$ python3 backup_ver2.py
Successfully created directory E:\Backup\20080702
Successful backup to E:\Backup\20080702\202311.zip
$ python3 backup_ver2.py
Successful backup to E:\Backup\20080702\202325.zip
How It Works:
Most of the program remains the same. The changes are that we check if there
is a directory with the current day as its name inside the main backup directory
using the os.path.exists function. If it doesn’t exist, we create it using the
os.mkdir function.
12.4
Third Version
The second version works fine when I do many backups, but when there are lots
of backups, I am finding it hard to differentiate what the backups were for! For
example, I might have made some major changes to a program or presentation,
then I want to associate what those changes are with the name of the zip archive.
80
This can be easily achieved by attaching a user-supplied comment to the name
of the zip archive.
Note
The following program does not work, so do not be alarmed, please follow
along because there’s a lesson in here.
Save as backup_ver3.py:
import
os
import
time
# 1. The files and directories to be backed up are specified in a list.
source = [
'"C:\\My Documents"'
,
'C:\\Code'
]
# Notice we had to use double quotes inside the string for names with spaces in it.
# 2. The backup must be stored in a main backup directory
target_dir =
'E:\\Backup'
# Remember to change this to what you will be using
# 3. The files are backed up into a zip file.
# 4. The current day is the name of the subdirectory in the main directory
today = target_dir + os.sep + time.strftime(
'%Y%m
%d
'
)
# The current time is the name of the zip archive
now = time.strftime(
'%H%M%S'
)
# Take a comment from the user to create the name of the zip file
comment =
input
(
'Enter a comment --> '
)
if
len
(comment) ==
0
:
# check if a comment was entered
target = today + os.sep + now +
'.zip'
else
:
target = today + os.sep + now +
'_'
+
comment.replace(
' '
,
'_'
) +
'.zip'
# Create the subdirectory if it isn't already there
if
not os.path.exists(today):
os.mkdir(today)
# make directory
(
'Successfully created directory'
, today)
# 5. We use the zip command to put the files in a zip archive
zip_command =
"zip -qr {0} {1}"
.
format
(target,
' '
.join(source))
# Run the backup
if
os.system(zip_command) ==
0
:
(
'Successful backup to'
, target)
else
:
(
'Backup FAILED'
)
81
Output:
$ python3 backup_ver3.py
File "backup_ver3.py", line 25
target = today + os.sep + now + '_' +
^
SyntaxError: invalid syntax
How This (does not) Work:
This program does not work!
Python says there is a syntax error which
means that the script does not satisfy the structure that Python expects to see.
When we observe the error given by Python, it also tells us the place where it
detected the error as well. So we start debugging our program from that line.
On careful observation, we see that the single logical line has been split into
two physical lines but we have not specified that these two physical lines belong
together. Basically, Python has found the addition operator (+) without any
operand in that logical line and hence it doesn’t know how to continue. Remember
that we can specify that the logical line continues in the next physical line by the
use of a backslash at the end of the physical line. So, we make this correction to
our program. This correction of the program when we find errors is called bug
fixing
.
12.5
Fourth Version
Save as backup_ver4.py:
import
os
import
time
# 1. The files and directories to be backed up are specified in a list.
source = [
'"C:\\My Documents"'
,
'C:\\Code'
]
# Notice we had to use double quotes inside the string for names with spaces in it.
# 2. The backup must be stored in a main backup directory
target_dir =
'E:\\Backup'
# Remember to change this to what you will be using
# 3. The files are backed up into a zip file.
# 4. The current day is the name of the subdirectory in the main directory
today = target_dir + os.sep + time.strftime(
'%Y%m
%d
'
)
# The current time is the name of the zip archive
now = time.strftime(
'%H%M%S'
)
# Take a comment from the user to create the name of the zip file
82
comment =
input
(
'Enter a comment --> '
)
if
len
(comment) ==
0
:
# check if a comment was entered
target = today + os.sep + now +
'.zip'
else
:
target = today + os.sep + now +
'_'
+ \
comment.replace(
' '
,
'_'
) +
'.zip'
# Create the subdirectory if it isn't already there
if
not os.path.exists(today):
os.mkdir(today)
# make directory
(
'Successfully created directory'
, today)
# 5. We use the zip command to put the files in a zip archive
zip_command =
"zip -qr {0} {1}"
.
format
(target,
' '
.join(source))
# Run the backup
if
os.system(zip_command) ==
0
:
(
'Successful backup to'
, target)
else
:
(
'Backup FAILED'
)
Output:
$ python3 backup_ver4.py
Enter a comment --> added new examples
Successful backup to E:\Backup\20080702\202836_added_new_examples.zip
$ python3 backup_ver4.py
Enter a comment -->
Successful backup to E:\Backup\20080702\202839.zip
How It Works:
This program now works! Let us go through the actual enhancements that we
had made in version 3. We take in the user’s comments using the input function
and then check if the user actually entered something by finding out the length
of the input using the len function. If the user has just pressed enter without
entering anything (maybe it was just a routine backup or no special changes
were made), then we proceed as we have done before.
However, if a comment was supplied, then this is attached to the name of the
zip archive just before the .zip extension. Notice that we are replacing spaces
in the comment with underscores - this is because managing filenames without
spaces is much easier.
83
12.6
More Refinements
The fourth version is a satisfactorily working script for most users, but there is
always room for improvement. For example, you can include a verbosity level for
the program where you can specify a -v option to make your program become
more talkative.
Another possible enhancement would be to allow extra files and directories to
be passed to the script at the command line. We can get these names from the
sys.argv list and we can add them to our source list using the extendmethod
provided by the list class.
The most important refinement would be to not use the os.system way of
creating archives and instead using the zipfile or tarfile built-in module
to create these archives. They are part of the standard library and available
already for you to use without external dependencies on the zip program to be
available on your computer.
However, I have been using the os.system way of creating a backup in the above
examples purely for pedagogical purposes, so that the example is simple enough
to be understood by everybody but real enough to be useful.
Can you try writing the fifth version that uses the
module instead of the
os.system call?
12.7
The Software Development Process
We have now gone through the various phases in the process of writing a
software. These phases can be summarised as follows:
1. What (Analysis)
2. How (Design)
3. Do It (Implementation)
4. Test (Testing and Debugging)
5. Use (Operation or Deployment)
6. Maintain (Refinement)
A recommended way of writing programs is the procedure we have followed in
creating the backup script: Do the analysis and design. Start implementing with
a simple version. Test and debug it. Use it to ensure that it works as expected.
Now, add any features that you want and continue to repeat the Do It-Test-Use
cycle as many times as required. Remember, Software is grown, not built.
12.8
Summary
We have seen how to create our own Python programs/scripts and the various
stages involved in writing such programs. You may find it useful to create your
84
own program just like we did in this chapter so that you become comfortable
with Python as well as problem-solving.
Next, we will discuss object-oriented programming.
13
Object Oriented Programming
In all the programs we wrote till now, we have designed our program around
functions i.e. blocks of statements which manipulate data. This is called the
procedure-oriented
way of programming. There is another way of organizing
your program which is to combine data and functionality and wrap it inside
something called an object. This is called the object oriented programming
paradigm. Most of the time you can use procedural programming, but when
writing large programs or have a problem that is better suited to this method,
you can use object oriented programming techniques.
Classes and objects are the two main aspects of object oriented programming. A
class
creates a new type where objects are instances of the class. An analogy is
that you can have variables of type int which translates to saying that variables
that store integers are variables which are instances (objects) of the int class.
Note for Static Language Programmers
Note that even integers are
treated as objects (of the int class). This is unlike C++ and Java (before
version 1.5) where integers are primitive native types. See help(int) for
more details on the class.
C# and Java 1.5 programmers will find this similar to the boxing and unboxing
concept.
Objects can store data using ordinary variables that belong to the object. Vari-
ables that belong to an object or class are referred to as fields. Objects can
also have functionality by using functions that belong to a class. Such functions
are called methods of the class. This terminology is important because it helps
us to differentiate between functions and variables which are independent and
those which belong to a class or object. Collectively, the fields and methods can
be referred to as the attributes of that class.
Fields are of two types - they can belong to each instance/object of the class
or they can belong to the class itself. They are called instance variables and
class variables
respectively.
A class is created using the class keyword. The fields and methods of the class
are listed in an indented block.
85
13.1
The self
Class methods have only one specific difference from ordinary functions - they
must have an extra first name that has to be added to the beginning of the
parameter list, but you do not give a value for this parameter when you call
the method, Python will provide it. This particular variable refers to the object
itself
, and by convention, it is given the name self.
Although, you can give any name for this parameter, it is strongly recommended
that you use the name self - any other name is definitely frowned upon. There
are many advantages to using a standard name - any reader of your program will
immediately recognize it and even specialized IDEs (Integrated Development
Environments) can help you if you use self.
Note for C++/Java/C# Programmers
The self in Python is equivalent
to the this pointer in C++ and the this reference in Java and C#.
You must be wondering how Python gives the value for self and why you don’t
need to give a value for it. An example will make this clear. Say you have a class
called MyClass and an instance of this class called myobject. When you call a
method of this object as myobject.method(arg1, arg2), this is automatically
converted by Python into MyClass.method(myobject, arg1, arg2) - this is
all the special self is about.
This also means that if you have a method which takes no arguments, then you
still have to have one argument - the self.
13.2
Classes
The simplest class possible is shown in the following example (save as
simplestclass.py).
class
Person:
pass
# An empty block
p = Person()
(p)
Output:
$ python3 simplestclass.py
<__main__.Person object at 0x019F85F0>
86
How It Works:
We create a new class using the class statement and the name of the class.
This is followed by an indented block of statements which form the body of the
class. In this case, we have an empty block which is indicated using the pass
statement.
Next, we create an object/instance of this class using the name of the class
followed by a pair of parentheses. (We will learn
in
the next section). For our verification, we confirm the type of the variable by
simply printing it. It tells us that we have an instance of the Person class in
the __main__ module.
Notice that the address of the computer memory where your object is stored
is also printed. The address will have a different value on your computer since
Python can store the object wherever it finds space.
13.3
Object Methods
We have already discussed that classes/objects can have methods just like
functions except that we have an extra self variable. We will now see an
example (save as method.py).
class
Person:
def
sayHi(
self
):
(
'Hello, how are you?'
)
p = Person()
p.sayHi()
# This short example can also be written as Person().sayHi()
Output:
$ python3 method.py
Hello, how are you?
How It Works:
Here we see the self in action. Notice that the sayHi method takes no parame-
ters but still has the self in the function definition.
13.4
The init method
There are many method names which have special significance in Python classes.
We will see the significance of the __init__ method now.
87
The __init__ method is run as soon as an object of a class is instantiated. The
method is useful to do any initialization you want to do with your object. Notice
the double underscores both at the beginning and at the end of the name.
Example (save as class_init.py):
class
Person:
def
__init__
(
self
, name):
self
.name = name
def
sayHi(
self
):
(
'Hello, my name is'
,
self
.name)
p = Person(
'Swaroop'
)
p.sayHi()
# This short example can also be written as Person('Swaroop').sayHi()
Output:
$ python3 class_init.py
Hello, my name is Swaroop
How It Works:
Here, we define the __init__ method as taking a parameter name (along with
the usual self). Here, we just create a new field also called name. Notice these
are two different variables even though they are both called ‘name’. There is no
problem because the dotted notation self.name means that there is something
called “name” that is part of the object called “self” and the other name is a
local variable. Since we explicitly indicate which name we are referring to, there
is no confusion.
Most importantly, notice that we do not explicitly call the __init__ method but
pass the arguments in the parentheses following the class name when creating a
new instance of the class. This is the special significance of this method.
Now, we are able to use the self.name field in our methods which is demonstrated
in the sayHi method.
13.5
Class And Object Variables
We have already discussed the functionality part of classes and objects (i.e. meth-
ods), now let us learn about the data part. The data part, i.e. fields, are nothing
but ordinary variables that are bound to the namespaces of the classes and
objects. This means that these names are valid within the context of these
classes and objects only. That’s why they are called name spaces.
88
There are two types of fields - class variables and object variables which are
classified depending on whether the class or the object owns the variables
respectively.
Class variables
are shared - they can be accessed by all instances of that class.
There is only one copy of the class variable and when any one object makes a
change to a class variable, that change will be seen by all the other instances.
Object variables
are owned by each individual object/instance of the class. In
this case, each object has its own copy of the field i.e. they are not shared and
are not related in any way to the field by the same name in a different instance.
An example will make this easy to understand (save as objvar.py):
class
Robot:
'''Represents a robot, with a name.'''
# A class variable, counting the number of robots
population =
0
def
__init__
(
self
, name):
'''Initializes the data.'''
self
.name = name
(
'(Initializing {0})'
.
format
(
self
.name))
# When this person is created, the robot
# adds to the population
Robot.population +=
1
def
__del__
(
self
):
'''I am dying.'''
(
'{0} is being destroyed!'
.
format
(
self
.name))
Robot.population -=
1
if
Robot.population ==
0
:
(
'{0} was the last one.'
.
format
(
self
.name))
else
:
(
'There are still {0:d} robots working.'
.
format
(Robot.population))
def
sayHi(
self
):
'''Greeting by the robot.
Yeah, they can do that.'''
(
'Greetings, my masters call me {0}.'
.
format
(
self
.name))
def
howMany():
'''Prints the current population.'''
89
(
'We have {0:d} robots.'
.
format
(Robot.population))
howMany =
staticmethod
(howMany)
droid1 = Robot(
'R2-D2'
)
droid1.sayHi()
Robot.howMany()
droid2 = Robot(
'C-3PO'
)
droid2.sayHi()
Robot.howMany()
(
"\nRobots can do some work here.\n"
)
(
"Robots have finished their work. So let's destroy them."
)
del
droid1
del
droid2
Robot.howMany()
Output:
$ python3 objvar.py
(Initializing R2-D2)
Greetings, my masters call me R2-D2.
We have 1 robots.
(Initializing C-3PO)
Greetings, my masters call me C-3PO.
We have 2 robots.
Robots can do some work here.
Robots have finished their work. So let's destroy them.
R2-D2 is being destroyed!
There are still 1 robots working.
C-3PO is being destroyed!
C-3PO was the last one.
We have 0 robots.
How It Works:
This is a long example but helps demonstrate the nature of class and object
variables. Here, population belongs to theRobot class and hence is a class
variable. The name variable belongs to the object (it is assigned using self) and
hence is an object variable.
Thus, we refer to the population class variable as Robot.population and not
as self.population. We refer to the object variable name using self.name
90
notation in the methods of that object. Remember this simple difference between
class and object variables. Also note that an object variable with the same name
as a class variable will hide the class variable!
The howMany is actually a method that belongs to the class and not to the
object. This means we can define it as either a classmethod or a staticmethod
depending on whether we need to know which class we are part of. Since we
don’t need such information, we will go for staticmethod .
We could have also achieved the same using
@staticmethod
def
howMany():
'''Prints the current population.'''
(
'We have {0:d} robots.'
.
format
(Robot.population))
Decorators can be imagined to be a shortcut to calling an explicit statement, as
we have seen in this example.
Observe that the __init__ method is used to initialize the Robot instance with
a name. In this method, we increase the population count by 1 since we have
one more robot being added. Also observe that the values of self.name is
specific to each object which indicates the nature of object variables.
Remember, that you must refer to the variables and methods of the same object
using the self only. This is called an attribute reference.
In this program, we also see the use of docstrings for classes as well as methods.
We can access the class docstring at runtime using Robot.__doc__ and the
method docstring as Robot.sayHi.__doc__
Just like the __init__ method, there is another special method __del__ which
is called when an object is going to die i.e. it is no longer being used and is
being returned to the computer system for reusing that piece of memory. In this
method, we simply decrease the Robot.population count by 1.
The __del__ method is run when the object is no longer in use and there is
no guarantee when that method will be run. If you want to explicitly see it in
action, we have to use the del statement which is what we have done here.
All class members are public. One exception: If you use data members with
names using the double underscore prefix such as __privatevar, Python uses
name-mangling to effectively make it a private variable.
Thus, the convention followed is that any variable that is to be used only within
the class or object should begin with an underscore and all other names are
public and can be used by other classes/objects. Remember that this is only
a convention and is not enforced by Python (except for the double underscore
prefix).
91
Note for C++/Java/C# Programmers
All class members (including the
data members) are public and all the methods are virtual in Python.
13.6
Inheritance
One of the major benefits of object oriented programming is reuse of code and
one of the ways this is achieved is through the inheritance mechanism. Inheritance
can be best imagined as implementing a type and subtype relationship between
classes.
Suppose you want to write a program which has to keep track of the teachers
and students in a college. They have some common characteristics such as name,
age and address. They also have specific characteristics such as salary, courses
and leaves for teachers and, marks and fees for students.
You can create two independent classes for each type and process them but adding
a new common characteristic would mean adding to both of these independent
classes. This quickly becomes unwieldy.
A better way would be to create a common class called SchoolMember and then
have the teacher and student classes inherit from this class i.e. they will become
sub-types of this type (class) and then we can add specific characteristics to
these sub-types.
There are many advantages to this approach. If we add/change any functionality
in SchoolMember, this is automatically reflected in the subtypes as well. For
example, you can add a new ID card field for both teachers and students by
simply adding it to the SchoolMember class. However, changes in the subtypes
do not affect other subtypes. Another advantage is that if you can refer to a
teacher or student object as a SchoolMember object which could be useful in
some situations such as counting of the number of school members. This is called
polymorphism
where a sub-type can be substituted in any situation where
a parent type is expected i.e. the object can be treated as an instance of the
parent class.
Also observe that we reuse the code of the parent class and we do not need to
repeat it in the different classes as we would have had to in case we had used
independent classes.
The SchoolMember class in this situation is known as the base class or the
superclass
. The Teacher and Student classes are called the derived classes or
subclasses
.
We will now see this example as a program (save as inherit.py):
class
SchoolMember:
'''Represents any school member.'''
def
__init__
(
self
, name, age):
92
self
.name = name
self
.age = age
(
'(Initialized SchoolMember: {0})'
.
format
(
self
.name))
def
tell(
self
):
'''Tell my details.'''
(
'Name:"{0}" Age:"{1}"'
.
format
(
self
.name,
self
.age), end=
" "
)
class
Teacher(SchoolMember):
'''Represents a teacher.'''
def
__init__
(
self
, name, age, salary):
SchoolMember.
__init__
(
self
, name, age)
self
.salary = salary
(
'(Initialized Teacher: {0})'
.
format
(
self
.name))
def
tell(
self
):
SchoolMember.tell(
self
)
(
'Salary: "{0:d}"'
.
format
(
self
.salary))
class
Student(SchoolMember):
'''Represents a student.'''
def
__init__
(
self
, name, age, marks):
SchoolMember.
__init__
(
self
, name, age)
self
.marks = marks
(
'(Initialized Student: {0})'
.
format
(
self
.name))
def
tell(
self
):
SchoolMember.tell(
self
)
(
'Marks: "{0:d}"'
.
format
(
self
.marks))
t = Teacher(
'Mrs. Shrividya'
,
40
,
30000
)
s = Student(
'Swaroop'
,
25
,
75
)
()
# prints a blank line
members = [t, s]
for
member in members:
member.tell()
# works for both Teachers and Students
Output:
$ python3 inherit.py
(Initialized SchoolMember: Mrs. Shrividya)
(Initialized Teacher: Mrs. Shrividya)
(Initialized SchoolMember: Swaroop)
93
(Initialized Student: Swaroop)
Name:"Mrs. Shrividya" Age:"40" Salary: "30000"
Name:"Swaroop" Age:"25" Marks: "75"
How It Works:
To use inheritance, we specify the base class names in a tuple following the class
name in the class definition. Next, we observe that the __init__ method of the
base class is explicitly called using the self variable so that we can initialize the
base class part of the object. This is very important to remember - Python does
not automatically call the constructor of the base class, you have to explicitly
call it yourself.
We also observe that we can call methods of the base class by prefixing the class
name to the method call and then pass in the self variable along with any
arguments.
Notice that we can treat instances of Teacher or Student as just instances of
the SchoolMember when we use the tell method of the SchoolMember class.
Also, observe that the tell method of the subtype is called and not the tell
method of the SchoolMember class. One way to understand this is that Python
always
starts looking for methods in the actual type, which in this case it does.
If it could not find the method, it starts looking at the methods belonging to its
base classes one by one in the order they are specified in the tuple in the class
definition.
A note on terminology - if more than one class is listed in the inheritance tuple,
then it is called multiple inheritance.
The end parameter is used in the tell() method to change a new line to be
started at the end of the print() call to printing spaces.
13.7
Summary
We have now explored the various aspects of classes and objects as well as the
various terminologies associated with it. We have also seen the benefits and
pitfalls of object-oriented programming. Python is highly object-oriented and
understanding these concepts carefully will help you a lot in the long run.
Next, we will learn how to deal with input/output and how to access files in
Python.
14
Input Output
There will be situations where your program has to interact with the user. For
example, you would want to take input from the user and then print some results
94
back. We can achieve this using the input() and print() functions respectively.
For output, we can also use the various methods of the str (string) class. For
example, you can use the rjust method to get a string which is right justified
to a specified width. See help(str) for more details.
Another common type of input/output is dealing with files. The ability to create,
read and write files is essential to many programs and we will explore this aspect
in this chapter.
14.1
Input from user
Save this program as user_input.py:
def
reverse(text):
return
text[::-
1
]
def
is_palindrome(text):
return
text == reverse(text)
something =
input
(
'Enter text: '
)
if
(is_palindrome(something)):
(
"Yes, it is a palindrome"
)
else
:
(
"No, it is not a palindrome"
)
Output:
$ python3 user_input.py
Enter text: sir
No, it is not a palindrome
$ python3 user_input.py
Enter text: madam
Yes, it is a palindrome
$ python3 user_input.py
Enter text: racecar
Yes, it is a palindrome
How It Works:
We use the slicing feature to reverse the text. We’ve already seen how we can
make
using the seq[a:b] code starting from position a
to position b. We can also provide a third argument that determines the step
95
by which the slicing is done. The default step is 1 because of which it returns a
continuous part of the text. Giving a negative step, i.e., -1 will return the text
in reverse.
The input() function takes a string as argument and displays it to the user.
Then it waits for the user to type something and press the return key. Once
the user has entered and pressed the return key, the input() function will then
return that text the user has entered.
We take that text and reverse it. If the original text and reversed text are equal,
then the text is a
Homework exercise
Checking whether a text is a palindrome should also
ignore punctuation, spaces and case. For example, “Rise to vote, sir.” is
also a palindrome but our current program doesn’t say it is. Can you
improve the above program to recognize this palindrome?
Hint (Don’t read) below
Use a tuple (you can find a list of all punctuation marks here
to hold all the forbidden characters, then use the membership test to
determine whether a character should be removed or not, i.e. forbidden =
(‘!’, ‘?’, ‘.’, . . . ).
14.2
Files
You can open and use files for reading or writing by creating an object of the
file class and using its read, readline or write methods appropriately to read
from or write to the file. The ability to read or write to the file depends on the
mode you have specified for the file opening. Then finally, when you are finished
with the file, you call the close method to tell Python that we are done using
the file.
Example (save as using_file.py):
poem =
'''\
Programming is fun
When the work is done
if you wanna make your work also fun:
use Python!
'''
f =
open
(
'poem.txt'
,
'w'
)
# open for 'w'riting
f.write(poem)
# write text to file
f.close()
# close the file
f =
open
(
'poem.txt'
)
# if no mode is specified, 'r'ead mode is assumed by default
96
while
True
:
line = f.readline()
if
len
(line) ==
0
:
# Zero length indicates EOF
break
(line, end=
''
)
f.close()
# close the file
Output:
$ python3 using_file.py
Programming is fun
When the work is done
if you wanna make your work also fun:
use Python!
How It Works:
First, open a file by using the built-in open function and specifying the name of
the file and the mode in which we want to open the file. The mode can be a
read mode (’r’), write mode (’w’) or append mode (’a’). We can also specify
whether we are reading, writing, or appending in text mode (’t’) or binary
mode (’b’). There are actually many more modes available and help(open)
will give you more details about them. By default, open() considers the file to
be a ’t’ext file and opens it in ’r’ead mode.
In our example, we first open the file in write text mode and use the write
method of the file object to write to the file and then we finally close the file.
Next, we open the same file again for reading. We don’t need to specify a mode
because ‘read text file’ is the default mode. We read in each line of the file using
the readline method in a loop. This method returns a complete line including
the newline character at the end of the line. When an empty string is returned,
it means that we have reached the end of the file and we ‘break’ out of the loop.
By default, the print() function prints the text as well as an automatic newline
to the screen. We are suppressing the newline by specifying end=” because the
line that is read from the file already ends with a newline character. Then, we
finally closethe file.
Now, check the contents of the poem.txt file to confirm that the program has
indeed written to and read from that file.
14.3
Pickle
Python provides a standard module called pickle using which you can store
any
Python object in a file and then get it back later. This is called storing the
object persistently.
97
Example (save as pickling.py):
import
pickle
# the name of the file where we will store the object
shoplistfile =
'shoplist.data'
# the list of things to buy
shoplist = [
'apple'
,
'mango'
,
'carrot'
]
# Write to the file
f =
open
(shoplistfile,
'wb'
)
pickle.dump(shoplist, f)
# dump the object to a file
f.close()
del
shoplist
# destroy the shoplist variable
# Read back from the storage
f =
open
(shoplistfile,
'rb'
)
storedlist = pickle.load(f)
# load the object from the file
(storedlist)
Output:
$ python3 pickling.py
['apple', 'mango', 'carrot']
How It Works:
To store an object in a file, we have to first open the file in ’w’rite ’b’inary mode
and then call the dump function of thepickle module. This process is called
pickling
.
Next, we retrieve the object using the load function of the pickle module which
returns the object. This process is called unpickling.
14.4
Summary
We have discussed various types of input/output and also file handling and using
the pickle module.
Next, we will explore the concept of exceptions.
98
15
Exceptions
Exceptions occur when certain exceptional situations occur in your program.
For example, what if you are going to read a file and the file does not exist?
Or what if you accidentally deleted it when the program was running? Such
situations are handled using exceptions.
Similarly, what if your program had some invalid statements? This is handled
by Python which raises its hands and tells you there is an error.
15.1
Errors
Consider a simple print function call. What if we misspelt print as Print?
Note the capitalization. In this case, Python raises a syntax error.
>>> Print('Hello World')
Traceback (most recent call last):
File "<pyshell#0>", line 1, in <module>
Print('Hello World')
NameError: name 'Print' is not defined
>>> print('Hello World')
Hello World
Observe that a NameError is raised and also the location where the error was
detected is printed. This is what an error handler for this error does.
15.2
Exceptions
We will try to read input from the user. Press ctrl-d and see what happens.
>>> s = input('Enter something --> ')
Enter something -->
Traceback (most recent call last):
File "<pyshell#2>", line 1, in <module>
s = input('Enter something --> ')
EOFError: EOF when reading a line
Python raises an error called EOFError which basically means it found an end
of file
symbol (which is represented by ctrl-d) when it did not expect to see it.
99
15.3
Handling Exceptions
We can handle exceptions using the try..except statement. We basically put
our usual statements within the try-block and put all our error handlers in the
except-block.
Example (save as try_except.py):
try
:
text =
input
(
'Enter something --> '
)
except
EOFError
:
(
'Why did you do an EOF on me?'
)
except
KeyboardInterrupt
:
(
'You cancelled the operation.'
)
else
:
(
'You entered {0}'
.
format
(text))
Output:
$ python3 try_except.py
Enter something -->
# Press ctrl-d
Why did you do an EOF on me?
$ python3 try_except.py
Enter something -->
# Press ctrl-c
You cancelled the operation.
$ python3 try_except.py
Enter something --> no exceptions
You entered no exceptions
How It Works:
We put all the statements that might raise exceptions/errors inside the try
block and then put handlers for the appropriate errors/exceptions in the except
clause/block. The except clause can handle a single specified error or exception,
or a parenthesized list of errors/exceptions. If no names of errors or exceptions
are supplied, it will handle all errors and exceptions.
Note that there has to be at least one except clause associated with every try
clause. Otherwise, what’s the point of having a try block?
If any error or exception is not handled, then the default Python handler is
called which just stops the execution of the program and prints an error message.
We have already seen this in action above.
You can also have an else clause associated with a try..except block. The
else clause is executed if no exception occurs.
100
In the next example, we will also see how to get the exception object so that we
can retrieve additional information.
15.4
Raising Exceptions
You can raise exceptions using the raise statement by providing the name of
the error/exception and the exception object that is to be thrown.
The error or exception that you can raise should be a class which directly or
indirectly must be a derived class of the Exception class.
Example (save as raising.py):
class
ShortInputException(
Exception
):
'''A user-defined exception class.'''
def
__init__
(
self
, length, atleast):
Exception
.
__init__
(
self
)
self
.length = length
self
.atleast = atleast
try
:
text =
input
(
'Enter something --> '
)
if
len
(text) <
3
:
raise
ShortInputException(
len
(text),
3
)
# Other work can continue as usual here
except
EOFError
:
(
'Why did you do an EOF on me?'
)
except
ShortInputException
as
ex:
(
'ShortInputException: The input was {0} long, expected at least {1}'
\
.
format
(ex.length, ex.atleast))
else
:
(
'No exception was raised.'
)
Output:
$ python3 raising.py
Enter something --> a
ShortInputException: The input was 1 long, expected at least 3
$ python3 raising.py
Enter something --> abc
No exception was raised.
How It Works:
101
Here, we are creating our own exception type. This new exception type is called
ShortInputException. It has two fields - length which is the length of the
given input, and atleast which is the minimum length that the program was
expecting.
In the except clause, we mention the class of error which will be stored as
the variable name to hold the corresponding error/exception object. This is
analogous to parameters and arguments in a function call. Within this particular
except clause, we use thelength and atleast fields of the exception object to
print an appropriate message to the user.
15.5
Try .. Finally
Suppose you are reading a file in your program. How do you ensure that the file
object is closed properly whether or not an exception was raised? This can be
done using the finally block. Note that you can use an except clause along
with a finally block for the same corresponding try block. You will have to
embed one within another if you want to use both.
Save as finally.py:
import
time
try
:
f =
open
(
'poem.txt'
)
while
True
:
# our usual file-reading idiom
line = f.readline()
if
len
(line) ==
0
:
break
(line, end=
''
)
time.sleep(
2
)
# To make sure it runs for a while
except
KeyboardInterrupt
:
(
'!! You cancelled the reading from the file.'
)
finally
:
f.close()
(
'(Cleaning up: Closed the file)'
)
Output:
$ python3 finally.py
Programming is fun
When the work is done
if you wanna make your work also fun:
!! You cancelled the reading from the file.
(Cleaning up: Closed the file)
102
How It Works:
We do the usual file-reading stuff, but we have arbitrarily introduced sleeping
for 2 seconds after printing each line using the time.sleep function so that the
program runs slowly (Python is very fast by nature). When the program is still
running, press ctrl-c to interrupt/cancel the program.
Observe that the KeyboardInterrupt exception is thrown and the program
quits. However, before the program exits, the finally clause is executed and the
file object is always closed.
15.6
The with statement
Acquiring a resource in the try block and subsequently releasing the resource in
the finally block is a common pattern. Hence, there is also a with statement
that enables this to be done in a clean manner:
Save as using_with.py:
with
open
(
"poem.txt"
)
as
f:
for
line in f:
(line, end=
''
)
How It Works:
The output should be same as the previous example. The difference here is that
we are using the open function with the with statement - we leave the closing of
the file to be done automatically by with open.
What happens behind the scenes is that there is a protocol used by the with
statement. It fetches the object returned by the open statement, let’s call it
“thefile” in this case.
It always calls the thefile.__enter__ function before starting the block of
code under it and always calls thefile.__exit__ after finishing the block of
code.
So the code that we would have written in a finally block should be taken care
of automatically by the __exit__method. This is what helps us to avoid having
to use explicit try..finally statements repeatedly.
More discussion on this topic is beyond scope of this book, so please refer
for a comprehensive explanation.
15.7
Summary
We have discussed the usage of the try..except and try..finally statements.
We have seen how to create our own exception types and how to raise exceptions
as well.
103
Next, we will explore the Python Standard Library.
16
Standard Library
The Python Standard Library contains a huge number of useful modules and is
part of every standard Python installation. It is important to become familiar
with the Python Standard Library since many problems can be solved quickly if
you are familiar with the range of things that these libraries can do.
We will explore some of the commonly used modules in this library. You can find
complete details for all of the modules in the Python Standard Library in the
of the documentation that comes with your Python
installation.
Let us explore a few useful modules.
Note
If you find the topics in this chapter too advanced, you may skip this
chapter. However, I highly recommend coming back to this chapter when
you are more comfortable with programming using Python.
16.1
sys module
The sys module contains system-specific functionality. We have already seen
that the sys.argv list contains the command-line arguments.
Suppose we want to check the version of the Python command being used so
that, say, we want to ensure that we are using at least version 3. The sys module
gives us such functionality.
$ python3
>>> import sys
>>> sys.version_info
sys.version_info(major=3, minor=3, micro=0, releaselevel='final', serial=0)
>>> sys.version_info.major >= 3
True
How It Works:
The sys module has a version_info tuple that gives us the version information.
The first entry is the major version. We can check this to, for example, ensure
the program runs only under Python 3.0:
Save as versioncheck.py:
104
import
sys, warnings
if
sys.version_info.major <
3
:
warnings.warn(
"Need Python 3.0 for this program to run"
,
RuntimeWarning
)
else
:
(
'Proceed as normal'
)
Output:
$ python2.7 versioncheck.py
versioncheck.py:6: RuntimeWarning: Need Python 3.0 for this program to run
RuntimeWarning)
$ python3 versioncheck.py
Proceed as normal
How It Works:
We use another module from the standard library called warnings that is used
to display warnings to the end-user. If the Python version number is not at least
3, we display a corresponding warning.
16.2
logging module
What if you wanted to have some debugging messages or important messages
to be stored somewhere so that you can check whether your program has been
running as you would expect it? How do you “store somewhere” these messages?
This can be achieved using the logging module.
Save as use_logging.py:
import
os, platform, logging
if
platform.platform().startswith(
'Windows'
):
logging_file = os.path.join(os.getenv(
'HOMEDRIVE'
), os.getenv(
'HOMEPATH'
),
'test.log'
)
else
:
logging_file = os.path.join(os.getenv(
'HOME'
),
'test.log'
)
(
"Logging to"
, logging_file)
logging.basicConfig(
level=logging.DEBUG,
format
=
'
%(asctime)s
:
%(levelname)s
:
%(message)s
'
,
filename = logging_file,
filemode =
'w'
,
105
)
logging.debug(
"Start of the program"
)
logging.info(
"Doing something"
)
logging.warning(
"Dying now"
)
Output:
$ python3 use_logging.py
Logging to C:\Users\swaroop\test.log
If we check the contents of test.log, it will look something like this:
2012-10-26 16:52:41,339 : DEBUG : Start of the program
2012-10-26 16:52:41,339 : INFO : Doing something
2012-10-26 16:52:41,339 : WARNING : Dying now
How It Works:
We use three modules from the standard library - the os module for interacting
with the operating system, the platform module for information about the
platform i.e. the operating system and the logging module to log information.
First, we check which operating system we are using by checking the string re-
turned by platform.platform() (for more information, see import platform;
help(platform)). If it is Windows, we figure out the home drive, the home
folder and the filename where we want to store the information. Putting these
three parts together, we get the full location of the file. For other platforms, we
need to know just the home folder of the user and we get the full location of the
file.
We use the os.path.join() function to put these three parts of the location
together. The reason to use a special function rather than just adding the strings
together is because this function will ensure the full location matches the format
expected by the operating system.
We configure the logging module to write all the messages in a particular format
to the file we have specified.
Finally, we can put messages that are either meant for debugging, information,
warning or even critical messages. Once the program has run, we can check this
file and we will know what happened in the program, even though no information
was displayed to the user running the program.
106
16.3
Module of the Week Series
There is much more to be explored in the standard library such as
and so on.
The best way to further explore the standard library is to read Doug Hellmann’s
excellent
series or reading the
16.4
Summary
We have explored some of the functionality of many modules in the Python
Standard Library. It is highly recommended to browse through the
Standard Library documentation
to get an idea of all the modules that are
available.
Next, we will cover various aspects of Python that will make our tour of Python
more complete.
17
More
So far we have covered a majority of the various aspects of Python that you
will use. In this chapter, we will cover some more aspects that will make our
knowledge of Python more well-rounded.
17.1
Passing tuples around
Ever wished you could return two different values from a function? You can. All
you have to do is use a tuple.
>>> def get_error_details():
...
return (2, 'second error details')
...
>>> errnum, errstr = get_error_details()
>>> errnum
2
>>> errstr
'second error details'
Notice that the usage of a, b = <some expression> interprets the result of
the expression as a tuple with two values.
If you want to interpret the results as (a, <everything else>), then you just
need to star it just like you would in function parameters:
107
>>> a, *b = [1, 2, 3, 4]
>>> a
1
>>> b
[2, 3, 4]
This also means the fastest way to swap two variables in Python is:
>>> a = 5; b = 8
>>> a, b = b, a
>>> a, b
(8, 5)
17.2
Special Methods
There are certain methods such as the __init__ and __del__ methods which
have special significance in classes.
Special methods are used to mimic certain behaviors of built-in types. For
example, if you want to use the x[key] indexing operation for your class (just
like you use it for lists and tuples), then all you have to do is implement the
__getitem__() method and your job is done. If you think about it, this is what
Python does for the list class itself!
Some useful special methods are listed in the following table. If you want to
know about all the special methods,
__init__(self, ...)
This method is called just before the newly created
object is returned for usage.
__del__(self)
Called just before the object is destroyed
__str__(self)
Called when we use the print function or when str()is used.
__lt__(self, other)
Called when the less than operator (<) is used. Similarly,
there are special methods for all the operators (+, >, etc.)
__getitem__(self, key)
Called when x[key] indexing operation is used.
__len__(self)
Called when the built-in len() function is used for the sequence
object.
108
17.3
Single Statement Blocks
We have seen that each block of statements is set apart from the rest by its own
indentation level. Well, there is one caveat. If your block of statements contains
only one single statement, then you can specify it on the same line of, say, a
conditional statement or looping statement. The following example should make
this clear:
>>> flag = True
>>> if flag: print('Yes')
Yes
Notice that the single statement is used in-place and not as a separate block. Al-
though, you can use this for making your program smaller, I strongly recommend
avoiding this short-cut method, except for error checking, mainly because it will
be much easier to add an extra statement if you are using proper indentation.
17.4
Lambda Forms
A lambda statement is used to create new function objects. Essentially, the
lambda takes a parameter followed by a single expression only which becomes
the body of the function and the value of this expression is returned by the new
function.
Example (save as lambda.py):
points = [ {
'x'
:
2
,
'y'
:
3
}, {
'x'
:
4
,
'y'
:
1
} ]
points.sort(key=
lambda
i : i[
'y'
])
(points)
Output:
[{'x': 4, 'y': 1}, {'x': 2, 'y': 3}]
How It Works:
Notice that the sort method of a list can take a key parameter which deter-
mines how the list is sorted (usually we know only about ascending or descending
order). In our case, we want to do a custom sort, and for that we need to write a
function but instead of writing a separate def block for a function that will get
used in only this one place, we use a lambda expression to create a new function.
109
17.5
List Comprehension
List comprehensions are used to derive a new list from an existing list. Suppose
you have a list of numbers and you want to get a corresponding list with all the
numbers multiplied by 2 only when the number itself is greater than 2. List
comprehensions are ideal for such situations.
Example (save as list_comprehension.py):
listone = [
2
,
3
,
4
]
listtwo = [
2
*i
for
i in listone
if
i >
2
]
(listtwo)
Output:
$ python3 list_comprehension.py
[6, 8]
How It Works:
Here, we derive a new list by specifying the manipulation to be done (2*i)
when some condition is satisfied (if i > 2). Note that the original list remains
unmodified.
The advantage of using list comprehensions is that it reduces the amount of
boilerplate code required when we use loops to process each element of a list
and store it in a new list.
17.6
Receiving Tuples and Dictionaries in Functions
There is a special way of receiving parameters to a function as a tuple or a
dictionary using the * or ** prefix respectively. This is useful when taking
variable number of arguments in the function.
>>> def powersum(power, *args):
...
'''Return the sum of each argument raised to
specified power.'''
...
total = 0
...
for i in args:
...
total += pow(i, power)
...
return total
...
>>> powersum(2, 3, 4)
25
>>> powersum(2, 10)
100
110
Because we have a * prefix on the args variable, all extra arguments passed to
the function are stored in args as a tuple. If a ** prefix had been used instead,
the extra parameters would be considered to be key/value pairs of a dictionary.
17.7
The assert statement
The assert statement is used to assert that something is true. For example, if
you are very sure that you will have at least one element in a list you are using
and want to check this, and raise an error if it is not true, then assert statement
is ideal in this situation. When the assert statement fails, an AssertionError
is raised.
>>> mylist = ['item']
>>> assert len(mylist) >= 1
>>> mylist.pop()
'item'
>>> mylist
[]
>>> assert len(mylist) >= 1
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AssertionError
The assert statement should be used judiciously. Most of the time, it is better
to catch exceptions, either handle the problem or display an error message to
the user and then quit.
17.8
Escape Sequences
Suppose, you want to have a string which contains a single quote (’), how will
you specify this string? For example, the string is What’s your name?. You
cannot specify ’What’s your name?’ because Python will be confused as to
where the string starts and ends. So, you will have to specify that this single
quote does not indicate the end of the string. This can be done with the help of
what is called an escape sequence. You specify the single quote as \’ - notice
the backslash. Now, you can specify the string as ’What\’s your name?’.
Another way of specifying this specific string would be "What’s your name?"
i.e. using double quotes. Similarly, you have to use an escape sequence for using
a double quote itself in a double quoted string. Also, you have to indicate the
backslash itself using the escape sequence \\.
What if you wanted to specify a two-line string? One way is to use a triple-
quoted string as shown
or you can use an escape sequence for the
newline character - \n to indicate the start of a new line. An example is This is
111
the first line\nThis is the second line. Another useful escape sequence
to know is the tab - \t. There are many more escape sequences but I have
mentioned only the most useful ones here.
One thing to note is that in a string, a single backslash at the end of the line
indicates that the string is continued in the next line, but no newline is added.
For example:
"This is the first sentence. \
This is the second sentence."
is equivalent to
"This is the first sentence. This is the second sentence."
17.8.1
Raw String
If you need to specify some strings where no special processing such as escape
sequences are handled, then what you need is to specify a raw string by prefixing
r or R to the string. An example is r"Newlines are indicated by \n".
Note for Regular Expression Users
Always use raw strings when dealing
with regular expressions. Otherwise, a lot of backwhacking may be required.
For example, backreferences can be referred to as ’\\1’ or r’\1’.
17.9
Summary
We have covered some more features of Python in this chapter and yet we haven’t
covered all the features of Python. However, at this stage, we have covered most
of what you are ever going to use in practice. This is sufficient for you to get
started with whatever programs you are going to create.
Next, we will discuss how to explore Python further.
18
What Next
If you have read this book thoroughly till now and practiced writing a lot of
programs, then you must have become comfortable and familiar with Python.
You have probably created some Python programs to try out stuff and to exercise
your Python skills as well. If you have not done it already, you should. The
question now is ‘What Next?’.
I would suggest that you tackle this problem:
112
Create your own command-line address-book program using which
you can browse, add, modify, delete or search for your contacts such
as friends, family and colleagues and their information such as email
address and/or phone number. Details must be stored for later
retrieval.
This is fairly easy if you think about it in terms of all the various stuff that we
have come across till now. If you still want directions on how to proceed, then
here’s a hint.
Hint (Don’t read without trying first)
Create a class to represent the per-
son’s information. Use a dictionary to store person objects with their name
as the key. Use the pickle module to store the objects persistently on your
hard disk. Use the dictionary built-in methods to add, delete and modify
the persons.
Once you are able to do this, you can claim to be a Python programmer. Now,
immediately
thanking me for this great book ;-). This step
is optional but recommended. Also, please consider
to
support the continued development of this book.
If you found that program easy, here’s another one:
Implement the
. This command will replace one
string with another in the list of files provided.
The replace command can be as simple or as sophisticated as you wish, from
simple string substitution to looking for patterns (regular expressions).
After that, below are some ways to continue your journey with Python:
18.1
Example Code
The best way to learn a programming language is to write a lot of code and read
a lot of code:
•
is an extremely valuable collection of recipes or tips on
how to solve certain kinds of problems using Python. This is a must-read
for every Python user.
•
is another excellent must-read guide to the
113
18.2
Questions and Answers
•
Official Python Dos and Don’ts
•
•
Norvig’s list of Infrequently Asked Questions
•
•
StackOverflow questions tagged with python
18.3
Tutorials
•
Awaretek’s comprehensive list of Python tutorials
18.4
Videos
•
18.5
Discussion
If you are stuck with a Python problem, and don’t know whom to ask, then the
is the best place to ask your question.
Make sure you do your homework and have tried solving the problem yourself
first.
18.6
News
If you want to learn what is the latest in the world of Python, then follow the
18.7
Installing libraries
There are a huge number of open source libraries at the
which you can use in your own programs.
To install and use these libraries, you can use
18.8
Graphical Software
Suppose you want to create your own graphical programs using Python. This
can be done using a GUI (Graphical User Interface) library with their Python
bindings. Bindings are what allow you to write programs in Python and use the
libraries which are themselves written in C or C++ or other languages.
There are lots of choices for GUI using Python:
114
Kivy
PyGTK
This is the Python binding for the GTK+ toolkit which is the foun-
dation upon which GNOME is built. GTK+ has many quirks in usage
but once you become comfortable, you can create GUI apps fast. The
Glade graphical interface designer is indispensable. The documentation is
yet to improve. GTK+ works well on Linux but its port to Windows is
incomplete. You can create both free as well as proprietary software using
GTK+. To get started, read the
PyQt
This is the Python binding for the Qt toolkit which is the foundation
upon which the KDE is built. Qt is extremely easy to use and very powerful
especially due to the Qt Designer and the amazing Qt documentation.
PyQt is free if you want to create open source (GPL’ed) software and you
need to buy it if you want to create proprietary closed source software.
Starting with Qt 4.5 you can use it to create non-GPL software as well.
To get started, read the
or the
wxPython
This is the Python bindings for the wxWidgets toolkit. wxPython
has a learning curve associated with it. However, it is very portable and
runs on Linux, Windows, Mac and even embedded platforms. There are
many IDEs available for wxPython which include GUI designers as well
such as
and the
GUI builder. You
can create free as well as proprietary software using wxPython. To get
started, read the
18.8.1
Summary of GUI Tools
For more choices, see the
GuiProgramming wiki page at the official python
Unfortunately, there is no one standard GUI tool for Python. I suggest that you
choose one of the above tools depending on your situation. The first factor is
whether you are willing to pay to use any of the GUI tools. The second factor is
whether you want the program to run only on Windows or on Mac and Linux or
all of them. The third factor, if Linux is a chosen platform, is whether you are a
KDE or GNOME user on Linux.
For a more detailed and comprehensive analysis, see Page 26 of the
18.9
Various Implementations
There are usually two parts a programming language - the language and the
software. A language is how you write something. The software is what actually
runs our programs.
115
We have been using the CPython software to run our programs. It is referred to
as CPython because it is written in the C language and is the Classical Python
interpreter
.
There are also other software that can run your Python programs:
A Python implementation that runs on the Java platform. This means
you can use Java libraries and classes from within Python language and
vice-versa.
A Python implementation that runs on the .NET platform. This
means you can use .NET libraries and classes from within Python language
and vice-versa.
A Python implementation written in Python! This is a research project
to make it fast and easy to improve the interpreter since the interpreter
itself is written in a dynamic language (as opposed to static languages such
as C, Java or C# in the above three implementations)
A Python implementation that is specialized for thread-
based performance.
There are also others such as
- a Python implementation written in
Common Lisp and
which is a port of IronPython to work on top of
a JavaScript interpreter which could mean that you can use Python (instead of
JavaScript) to write your web-browser (“Ajax”) programs.
Each of these implementations have their specialized areas where they are useful.
18.10
Functional Programming (for advanced readers)
When you start writing larger programs, you should definitely learn more about
a functional approach to programming as opposed to the class-based approach
to programming that we learned in the
object-oriented programming chapter
•
Functional Programming Howto by A.M. Kuchling
•
Functional programming chapter in ‘Dive Into Python’ book
•
Functional Programming with Python presentation
18.11
Summary
We have now come to the end of this book but, as they say, this is the the
beginning of the end
!. You are now an avid Python user and you are no doubt
ready to solve many problems using Python. You can start automating your
computer to do all kinds of previously unimaginable things or write your own
games and much much more. So, get started!
116
19
FLOSS
Free/Libre and Open Source Software, in short,
is based on the concept of
a community, which itself is based on the concept of sharing, and particularly the
sharing of knowledge. FLOSS are free for usage, modification and redistribution.
If you have already read this book, then you are already familiar with FLOSS
since you have been using Python all along and Python is an open source
software!
Here are some examples of FLOSS to give an idea of the kind of things that
community sharing and building can create:
This is a FLOSS OS kernel used in the GNU/Linux operating system.
Linux, the kernel, was started by Linus Torvalds as a student. Android is
based on Linux. Any website you use these days will mostly be running
on Linux.
This is a community-driven distribution, sponsored by Canonical and
it is the most popular Linux distribution today. It allows you to install
a plethora of FLOSS available and all this in an easy-to-use and easy-to-
install manner. Best of all, you can just reboot your computer and run
GNU/Linux off the CD! This allows you to completely try out the new OS
before installing it on your computer. However, Ubuntu is not entirely free
software; it contains proprietary drivers, firmware, and applications.
This is an excellent community-driven and developed office suite
with a writer, presentation, spreadsheet and drawing components among
other things. It can even open and edit MS Word and MS PowerPoint files
with ease. It runs on almost all platforms and is entirely free, libre and
open source software.
This is the best web browser. It is blazingly fast and has gained
critical acclaim for its sensible and impressive features. The extensions
concept allows any kind of plugins to be used.
Its companion product
is an excellent email client that makes
reading email a snap.
This is an open source implementation of the Microsoft .NET platform. It
allows .NET applications to be created and run on GNU/Linux, Windows,
FreeBSD, Mac OS and many other platforms as well.
This is the popular open source web server. In fact, it is
the
most popular web server on the planet! It runs nearly more than half
of the websites out there. Yes, that’s right - Apache handles more websites
than all the competition (including Microsoft IIS) combined.
This is a video player that can play anything from DivX to MP3
to Ogg to VCDs and DVDs to . . . who says open source ain’t fun? ;-)
117
This list is just intended to give you a brief idea - there are many more excellent
FLOSS out there, such as the Perl language, PHP language, Drupal content
management system for websites, PostgreSQL database server, TORCS racing
game, KDevelop IDE, Xine - the movie player, VIM editor, Quanta+ editor,
Banshee audio player, GIMP image editing program, . . . This list could go on
forever.
To get the latest buzz in the FLOSS world, check out the following websites:
•
•
•
•
Visit the following websites for more information on FLOSS:
•
•
•
•
So, go ahead and explore the vast, free and open world of FLOSS!
20
Colophon
Almost all of the software that I have used in the creation of this book are
20.1
Birth of the Book
In the first draft of this book, I had used Red Hat 9.0 Linux as the foundation
of my setup and in the sixth draft, I used Fedora Core 3 Linux as the basis of
my setup.
Initially, I was using KWord to write the book (as explained in the
in the preface).
20.2
Teenage Years
Later, I switched to DocBook XML using Kate but I found it too tedious. So,
I switched to OpenOffice which was just excellent with the level of control it
118
provided for formatting as well as the PDF generation, but it produced very
sloppy HTML from the document.
Finally, I discovered XEmacs and I rewrote the book from scratch in DocBook
XML (again) after I decided that this format was the long term solution.
In the sixth draft, I decided to use Quanta+ to do all the editing. The standard
XSL stylesheets that came with Fedora Core 3 Linux were being used. However,
I had written a CSS document to give color and style to the HTML pages. I had
also written a crude lexical analyzer, in Python of course, which automatically
provides syntax highlighting to all the program listings.
For this seventh draft, I’m using
as the basis of my
. Now I
edit everything online and the readers can directly read/edit/discuss within the
wiki website.
I used Vim for editing thanks to the
ViewSourceWith extension for Firefox
that
integrates with Vim.
20.3
Now
Using
, and Mac OS X.
20.4
About The Author
http://www.swaroopch.com/about/
21
Revision History
• 2.0
–
20 Oct 2012
–
Rewritten in
, thanks to my wife who did most of the
conversion from the Mediawiki format
–
Simplifying text, removing non-essential sections such as nonlocal
and metaclasses
• 1.90
–
04 Sep 2008 and still in progress
–
Revival after a gap of 3.5 years!
–
Rewriting for Python 3.0
–
Rewrite using
(again)
• 1.20
–
13 Jan 2005
119
–
Complete rewrite using
on
Core 3 with lot of correc-
tions and updates. Many new examples. Rewrote my DocBook setup
from scratch.
• 1.15
–
28 Mar 2004
–
Minor revisions
• 1.12
–
16 Mar 2004
–
Additions and corrections.
• 1.10
–
09 Mar 2004
–
More typo corrections, thanks to many enthusiastic and helpful read-
ers.
• 1.00
–
08 Mar 2004
–
After tremendous feedback and suggestions from readers, I have made
significant revisions to the content along with typo corrections.
• 0.99
–
22 Feb 2004
–
Added a new chapter on modules. Added details about variable
number of arguments in functions.
• 0.98
–
16 Feb 2004
–
Wrote a Python script and CSS stylesheet to improve XHTML output,
including a crude-yet-functional lexical analyzer for automatic VIM-
like syntax highlighting of the program listings.
• 0.97
–
13 Feb 2004
–
Another completely rewritten draft, in DocBook XML (again). Book
has improved a lot - it is more coherent and readable.
• 0.93
–
25 Jan 2004
–
Added IDLE talk and more Windows-specific stuff
• 0.92
–
05 Jan 2004
–
Changes to few examples.
120
• 0.91
–
30 Dec 2003
–
Corrected typos. Improvised many topics.
• 0.90
–
18 Dec 2003
–
Added 2 more chapters.
format with revisions.
• 0.60
–
21 Nov 2003
–
Fully rewritten and expanded.
• 0.20
–
20 Nov 2003
–
Corrected some typos and errors.
• 0.15
–
20 Nov 2003
–
Converted to
with XEmacs.
• 0.10
–
14 Nov 2003
–
Initial draft using
22
Translations
There are many translations of the book available in different human languages,
thanks to many tireless volunteers!
If you want to help with these translations, please see the list of volunteers and
languages below and decide if you want to start a new translation or help in
existing translation projects.
If you plan to start a new translation, please read the
22.1
Arabic
Below is the link for the Arabic version. Thanks to Ashraf Ali Khalaf for
translating the book, you can read the whole book online
or you can
download it from
for more info
121
22.2
Brazilian Portuguese
There are two translations:
(samuel.arataca-at-gmail-dot-com) made the first Brazilian
Portuguese translation of this book when Python was in 2.3.5 version.
Samuel’s translation is available at
(rodrigoamaral-at-gmail-dot-com) has volunteered to translate
the book to Brazilian Portuguese.
Rodrigo’s translation is available at
http://www.swaroopch.org/notes/Python_
22.3
Catalan
Moises Gomez (moisesgomezgiron-at-gmail-dot-com) has volunteered to translate
the book to Catalan. The translation is in progress, and was present in the
Moisès Gómez - I am a developer and also a teacher of programming
(normally for people without any previous experience).
Some time ago I needed to learn how to program in Python, and
Swaroop’s work was really helpful. Clear, concise, and complete
enough. Just what I needed.
After this experience, I thought some other people in my country
could take benefit from it too. But English language can be a barrier.
So, why not try to translate it? And I did for a previous version of
BoP.
I my country there are two official languages. I selected the Catalan
language assuming that others will translate it to the more widespread
Spanish.
22.4
Chinese
Here’s a Chinese version at
http://www.swaroopch.org/notes/Python_cn:Table_
Juan Shen (orion-underscore-val-at-163-dot-com) has volunteered to translate
the book to Chinese. It is available at
http://www.pycn.org/python%E5%9C%
I am a postgraduate at Wireless Telecommunication Graduate School,
Beijing University of Technology, China PR. My current research
122
interest is on the synchronization, channel estimation and multi-
user detection of multicarrier CDMA system. Python is my major
programming language for daily simulation and research job, with
the help of Python Numeric, actually. I learned Python just half a
year before, but as you can see, it’s really easy-understanding, easy-
to-use and productive. Just as what is ensured in Swaroop’s book,
‘It’s my favorite programming language now’. ‘A Byte of Python’
is my tutorial to learn Python. It’s clear and effective to lead you
into a world of Python in the shortest time. It’s not too long, but
efficiently covers almost all important things in Python. I think
‘A Byte of Python’ should be strongly recommendable for newbies
as their first Python tutorial. Just dedicate my translation to the
potential millions of Python users in China.
22.5
Chinese Traditional
Fred Lin (gasolin-at-gmail-dot-com) has volunteered to translate the book to
Chinese Traditional.
It is available at
http://code.google.com/p/zhpy/wiki/ByteOfZhpy
An exciting feature of this translation is that it also contains the executable
chinese python sources
side by side with the original python sources.
Fred Lin
- I’m working as a network firmware engineer at Delta
Network, and I’m also a contributor of TurboGears web framework.
As a python evangelist (:-p), I need some material to promote python
language. I found ‘A Byte of Python’ hit the sweet point for both
newbies and experienced programmers. ‘A Byte of Python’ elaborates
the python essentials with affordable size.
The translation are originally based on simplified chinese version,
and soon a lot of rewrite were made to fit the current wiki version
and the quality of reading.
The recent chinese traditional version also featured with executable
chinese python sources, which are achieved by my new ‘zhpy’ (python
in chinese) project (launch from Aug 07).
zhpy(pronounce (Z.H.?, or zippy) build a layer upon python to
translate or interact with python in chinese(Traditional or Simplified).
This project is mainly aimed for education.
22.6
French
Gregory (coulix-at-ozforces-dot-com-dot-au) has volunteered to translate the
book to French.
123
Gérard Labadie (Palmipede) has completed to translate the book to French,
it starts with
http://www.swaroopch.org/notes/Python_fr:Table_des_Mati%
22.7
German
Lutz Horn (lutz-dot-horn-at-gmx-dot-de), Bernd Hengelein (bernd-dot-hengelein-
at-gmail-dot-com) and Christoph Zwerschke (cito-at-online-dot-de) have volun-
teered to translate the book to German.
Their translation is located at
Lutz Horn
says:
I’m 32 years old and have a degree of Mathematics from University of
Heidelberg, Germany. Currently I’m working as a software engineer
on a publicly funded project to build a web portal for all things
related to computer science in Germany.The main language I use
as a professional is Java, but I try to do as much as possible with
Python behind the scenes. Especially text analysis and conversion
is very easy with Python. I’m not very familiar with GUI toolkits,
since most of my programming is about web applications, where the
user interface is build using Java frameworks like Struts. Currently
I try to make more use of the functional programming features of
Python and of generators. After taking a short look into Ruby, I was
very impressed with the use of blocks in this language. Generally
I like the dynamic nature of languages like Python and Ruby since
it allows me to do things not possible in more static languages like
Java.I’ve searched for some kind of introduction to programming,
suitable to teach a complete non-programmer. I’ve found the book
‘How to Think Like a Computer Scientist: Learning with Python’,
and ‘Dive into Python’. The first is good for beginners but to long
to translate. The second is not suitable for beginners. I think ‘A
Byte of Python’ falls nicely between these, since it is not too long,
written to the point, and at the same time verbose enough to teach
a newbie. Besides this, I like the simple DocBook structure, which
makes translating the text a generation the output in various formats
a charm.
Bernd Hengelein
says:
Lutz and me are going to do the german translation together. We
just started with the intro and preface but we will keep you informed
about the progress we make. Ok, now some personal things about
me. I am 34 years old and playing with computers since the 1980’s,
124
when the “Commodore C64” ruled the nurseries. After studying
computer science I started working as a software engineer. Currently
I am working in the field of medical imaging for a major german
company. Although C++ is the main language I (have to) use for my
daily work, I am constantly looking for new things to learn.Last year
I fell in love with Python, which is a wonderful language, both for its
possibilities and its beauty. I read somewhere in the net about a guy
who said that he likes python, because the code looks so beautiful.
In my opinion he’s absolutly right. At the time I decided to learn
python, I noticed that there is very little good documentation in
german available. When I came across your book the spontaneous
idea of a german translation crossed my mind. Luckily, Lutz had the
same idea and we can now divide the work.I am looking forward to
a good cooperation!
22.8
Greek
The Greek Ubuntu Community
, for use in our
on-line asynchronous Python lessons that take place in our forums. Contact
for more information.
22.9
Indonesian
Daniel (daniel-dot-mirror-at-gmail-dot-com) is translating the book to Indonesian
at
http://python.or.id/moin.cgi/ByteofPython
W. Priyambodo also has volunteered to translate the book to Indonesian. The
translation is in progress and here is the
http://www.swaroopch.org/notes/
22.10
Italian
Enrico Morelli (mr-dot-mlucci-at-gmail-dot-com) and Massimo Lucci (morelli-at-
cerm-dot-unifi-dot-it) have volunteered to translate the book to Italian.
The Italian translation is present at
www.gentoo.it/Programmazione/byteofpython
The new translation is in progress and start with
Massimo Lucci and Enrico Morelli
- we are working at the Uni-
versity of Florence (Italy) - Chemistry Department. I (Massimo)
as service engineer and system administrator for Nuclear Magnetic
Resonance Spectrometers; Enrico as service engineer and system
administrator for our CED and parallel / clustered systems. We are
125
programming on python since about seven years, we had experience
working with Linux platforms since ten years. In Italy we are respon-
sible and administrator for www.gentoo.it web site for Gentoo/Linux
distrubution and www.nmr.it (now under construction) for Nuclear
Magnetic Resonance applications and Congress Organization and
Managements.That’s all! We are impressed by the smart language
used on your Book and we think this is essential for approaching the
Python to new users (we are thinking about hundred of students and
researcher working on our labs).
22.11
Japanese
Here’s a Japanese version at
http://www.swaroopch.org/notes/Python_ja:
Shunro Dozono (dozono-at-gmail-dot-com) is translating the book to Japanese.
22.12
Mongolian
Ariunsanaa Tunjin (luftballons2010-at-gmail-dot-com) has volunteered to trans-
late the book to Mongolian.
Update on Nov 22, 2009
: Ariunsanaa is on the verge of completing the transla-
tion.
22.13
Norwegian (bokmål)
Eirik Vågeskar (
http://www.swaroopch.org/notes/User:Vages
) is a high school
student at
in Norway, a
and currently
translating the book to Norwegian (bokmål). The translation is in progress,
and you can check the
http://www.swaroopch.org/notes/Python_nb-no:
for more details.
Eirik Vågeskar
: I have always wanted to program, but because I
speak a small language, the learning process was much harder. Most
tutorials and books are written in very technical English, so most high
school graduates will not even have the vocabulary to understand
what the tutorial is about. When I discovered this book, all my
problems were solved. “A Byte of Python” used simple non-technical
language to explain a programming language that is just as simple,
and these two things make learning Python fun. After reading half
of the book, I decided that the book was worth translating. I hope
the translation will help people who have found themself in the same
situation as me (especially young people), and maybe help spread
interest for the language among people with less technical knowledge.
126
22.14
Polish
Dominik Kozaczko (dkozaczko-at-gmail-dot-com) has volunteered to translate
the book to Polish. Translation is in progress and it’s main page is available
here:
Update
: The translation is complete and ready as of Oct 2, 2009. Thanks to
Dominik, his two students and their friend for their time and effort!
Dominik Kozaczko
- I’m a Computer Science and Information Tech-
nology teacher.
22.15
Portuguese
Fidel Viegas (fidel-dot-viegas-at-gmail-dot-com) has volunteered to translate the
book to Portuguese.
22.16
Romanian
Paul-Sebastian Manole (brokenthorn-at-gmail-dot-com) has volunteered to trans-
late this book to Romanian.
Paul-Sebastian Manole
- I’m a second year Computer Science student
at Spiru Haret University, here in Romania. I’m more of a self-taught
programmer and decided to learn a new language, Python. The
web told me there was no better way to do so but read ‘’A Byte of
Python”. That’s how popular this book is (congratulations to the
author for writing such an easy to read book). I started liking Python
so I decided to help translate the latest version of Swaroop’s book in
Romanian. Although I could be the one with the first initiative, I’m
just one volunteer so if you can help, please join me.
The translation is being done
http://www.swaroopch.org/notes/Python_ro
22.17
Russian and Ukranian
Averkiev Andrey (averkiyev-at-ukr-dot-net) has volunteered to translate the
book to Russian, and perhaps Ukranian (time permitting).
Vladimir Smolyar (v_2e-at-ukr-dot-net) has started a Russian translation wiki
pages. You may read the development version at
notes/Python_ru:Table_of_Contents
127
22.18
Slovak
Albertio Ward (albertioward-at-gmail-dot-com) has translated the book to Slovak
at
fatcow.com/edu/python-swaroopch-sl/
:
We are a non-profit organization called “Translation for education”.
We represent a group of people, mainly students and professors, of the
Slavonic University. Here are students from different departments:
linguistics, chemistry, biology, etc. We try to find interesting publica-
tions on the Internet that can be relevant for us and our university
colleagues. Sometimes we find articles by ourselves; other times our
professors help us choose the material for translation. After obtaining
permission from authors we translate articles and post them in our
blog which is available and accessible to our colleagues and friends.
These translated publications often help students in their daily study
routine.
Why have I chosen your article for translation? It was made to help
the Bulgarians understand this article in all possible detail. Having
done some research concerning the novelty and relevance of topics, I
found that it was quite urgent for those who live in my country. So,I
think it can become very popular. The language barrier in this little
case no longer exists, because it was eliminated by my translation.
22.19
Spanish
Alfonso de la Guarda Reyes (alfonsodg-at-ictechperu-dot-net), Gustavo
Echeverria (gustavo-dot-echeverria-at-gmail-dot-com), David Crespo Ar-
royo (davidcrespoarroyo-at-hotmail-dot-com) and Cristian Bermudez Serna
(crisbermud-at-hotmail-dot-com) have volunteered to translate the book to
Spanish. The translation is in progress, you can read the spanish (argentinian)
translation starting by the
http://www.swaroopch.org/notes/Python_es-ar:
Gustavo Echeverria
says:
I work as a software engineer in Argentina. I use mostly C# and
.Net technologies at work but strictly Python or Ruby in my personal
projects. I knew Python many years ago and I got stuck inmediately.
Not so long after knowing Python I discovered this book and it
helped me to learn the language. Then I volunteered to translate the
book to Spanish. Now, after receiving some requests, I’ve begun to
translate “A Byte of Python” with the help of Maximiliano Soler.
Cristian Bermudez Serna
says:
128
I am student of Telecommunications engineering at the University
of Antioquia (Colombia). Months ago, i started to learn Python
and found this wonderful book, so i volunteered to get the Spanish
translation.
22.20
Swedish
Mikael Jacobsson (leochingkwake-at-gmail-dot-com) has volunteered to translate
the book to Swedish.
22.21
Turkish
Türker SEZER (tsezer-at-btturk-dot-net) and Bugra Cakir (bugracakir-at-gmail-
dot-com) have volunteered to translate the book to Turkish. Where is Turkish
version? Bitse de okusak.
Note
: Replace -at- with @ , -dot- with . and -underscore- with _ in the
email addresses mentioned on this page. Dashes in other places in the email
address remain as-is.
23
Translation Howto
The full source of the book is available from the Git repository
Please
Then, fetch the repository to your computer. You need to know how to use
to do that.
Start editing the .pd files to your local language. Please read the
to understand the formatting of the text.
Then follow the instructions in the
to install the software required to
be able to convert the raw source files into PDFs, etc.
129
Document Outline
- A Byte of Python
- Preface
- Introduction
- Installation
- First Steps
- Basics
- Operators and Expressions
- Control Flow
- Functions
- Modules
- Data Structures
- Problem Solving
- Object Oriented Programming
- Input Output
- Exceptions
- Standard Library
- More
- What Next
- FLOSS
- Colophon
- Revision History
- Translations
- Translation Howto
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